International Journal of Hospitality Management 30 (2011) 262–271
Contents lists available at ScienceDirect
International Journal of Hospitality Management
journal homepage: www.elsevier.com/locate/ijhosman
The relationships between CRM, RQ, and CLV based on different
hotel preferences
Shwu-Ing Wu ∗ , Pei-Chi Li
National Chin-Yi University of Technology, Department of Business Administration, Taiwan, ROC
a r t i c l e
i n f o
Keywords:
Customer Relationship Management
Relationship Quality
Customer Lifetime Value
a b s t r a c t
This study uses Structural Equation Modeling (SEM) to investigate the strength of the relationships among
Customer Relationship Management (CRM), Relationship Quality (RQ), and Customer Lifetime Value (CLV)
from a consumer viewpoint. This study also investigates whether or not these relationship models show
significant differences based on different hotel type preference groups.
An analysis of 688 effective questionnaires produces two main findings. (1) CRM has a positive influence
on RQ, and RQ has a positive influence on CLV. (2) Consumer groups with different hotel preferences reveal
a partial interference effect on the relationships among CRM, RQ, and CLV. In other words, different hotel
preferences create significant differences in the strength of partial relationship paths.
© 2010 Elsevier Ltd. All rights reserved.
1. Introduction
An enterprise which set up a Customer Relationship Management (CRM) system to find and keep its best customers and
develop long-term relationships with loyal customers will acquire
greater profits (Christy et al., 1996). Therefore, CRM has gradually
been applied to the hotel industries to enhance the relationship
between enterprise and its customers (Liu et al., 2007). Because
the enterpriser believes that the relationship between a hotel and
its customers is direct and intimate, the positive effects of CRM
will significantly enhance the Relationship Quality (RQ) between
hotel industries and their customers, increasing the hotel’s Customer Lifetime Value (CLV) (Garbarino and Johnson, 1999; Kim and
Cha, 2002; Leu and Hsieh, 2000). However, based on the customer’s
viewpoint, few studies have explored if these relationships exist;
this is the major issue of this study.
The competition in hotel industries is quite severe, thus hotels
must improve their quality and services to win new customers.
In addition to attracting more customers, hotels must also maintain the loyalty of existing customers because the cost of gaining
new customers is approximately five times greater than the cost of
keeping old customers (Rosenberg and Czepiel, 1984). As a result,
CRM has become a hot topic in the hotel industry. In the customeroriented era, customers hold the key to a hotel’s fate, and good
customer relationships have become an important intangible asset
for hospitality companies. A hotel must realize the real needs of its
customers before it can effectively seize new business opportunities. Moreover, the relationship between a hotel and its customers
is inseparable, making CRM a very important factor in maintaining
RQ and enhancing CLV.
Although most hotel enterprises make great efforts to improve
their CRM practices to satisfy the needs of their customers, few
enterprises know how much customers feel the effects of CRM
actions. Therefore, this study investigates the influence of CRM on
RQ factors such as customer satisfaction, trust and commitment
in the hotel industry. This study also examines whether or not
RQ enhances CLV factors such as customer usage quantity, loyalty,
word of mouth, and purchase intentions.
Most previous studies on CRM or CLV are based on the enterprise’s point of view (e.g. Jae et al., 2004; Khirallah, 1999; Swift,
2001). However, this study takes the customer’s viewpoint to investigate the implementation of CRM practices by a hotel, whether or
not the RQ with customers will be improved, and whether or not
the CLV can be further enhanced. In addition, this study investigates
differences in the relationships among CRM, RQ, and CLV based on
different hotel type preferences.
Based on the research background and motivations that explore
if relationships exist between CRM, RQ, and CLV based on the customer’s viewpoint, the following describes the research objectives
of this study:
∗ Corresponding author at: National Chin-Yi University of Technology, Department of Business Administration, No. 35, Lane 215, Section 1, Chungshan Road,
Taiping, Taichung 411, Taiwan, ROC. Tel.: +886 4 23924505; fax: +886 4 23929584.
E-mail address: [email protected] (S.-I. Wu).
1. To investigate the influence of CRM on RQ.
2. To investigate the influence of RQ on CLV.
3. To investigate differences in the relationships between CRM, RQ,
and CLV based on different hotel type preferences.
0278-4319/$ – see front matter © 2010 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ijhm.2010.09.011
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
This study uses literature review to develop the research framework and questionnaire; then empirical study is used to produce
its results. The hotel industry can use these results as a reference
for employing CRM strategies.
2. Literature review and hypotheses
2.1. Customer Relationship Management (CRM)
Spengler (1999) proposed that CRM should really be called Contact Management, which represents the specific collection of all
information on the interaction between the customer and the company. A CRM system includes call center, database and customer
care functions that support data analysis. CRM is an enterpriselevel strategy and business model that is based on the customer as
the core, and uses information as a fulfillment tool. The major goal
of CRM is to satisfy customer needs in time, to build strong and long
term relationships with customers, and to increase business profit.
In areas of severe enterprise competition, any business operation
that strengthens customer loyalty is an indispensable competitive
advantage.
CRM represents the relationship between an enterprise and
the customer, and the key is the “relationship.” In other words,
an enterprise can positively affect customer behavior through
effective communication and understanding. CRM can reinforce
an organization’s capability in acquiring customers, keeping customers and enhancing the value of customers. Therefore, the
objective of CRM is to seize appropriate opportunities, and through
appropriate channels, provide appropriate products and services
to the appropriate customers. These measures make it possible to
increase interactive opportunities (Swift, 2001).
CRM is a commercial strategy for sales and service in which
an enterprise serves its customers. Whenever there is this kind of
interactive relationship, a company’s messages will be exchanged
with the appropriate customers (Kandell, 2000; Khirallah, 1999).
Linoff (1999) pointed out that the objective of CRM is to keep customers that contribute to the enterprise, which is also a continuous
improvement process. Swift (2001) proposed that CRM is a behavior in which an enterprise tries to understand and reach customers
through full interaction; moreover, it is a business strategy that
enhances customer loyalty and profit gaining.
2.2. Measurement of CRM
This study uses the customer’s perspective to investigate
whether or not the customer is aware of CRM practices implemented by a hotel. This requires evaluating the level of consumer
awareness of the presence of CRM actions by the hotel. Ming and
Chen (2002) and Keeney (1999) found that customers’ needs for
CRM actions include more diversified service channels, greater
trust in hotel service, low service cost, quick access to services,
extended service hours, easy access to services, privacy protection,
and customized service. This study modifies the variables above
to fit the hotel industry, and uses these items as CRM variables to
evaluate customer’s awareness of CRM practices in hotels.
2.3. Relationship Quality (RQ)
Hennig-Thurau and Klee (1997) proposed that RQ represents
the relationship between the customer and the enterprise, and
this relationship depends on the level of customer satisfaction.
Gummsson (1987) and Lee and Kim (1999) pointed out that RQ
is the interaction quality between enterprise and customer, and
can help to develop long term relationships. Crosby et al. (1990)
found that when sales personnel emphasize RQ, they can reduce
the insecurity and uncertainty experienced by the customer. This
263
in turn can generate customer trust and confidence in the future
performance of sales personnel, and will affect customer interactions in the future. Kumar et al. (1995) proposed that RQ reflects
customer trust, commitment, conflict, expectation of continuity,
and willingness to invest.
Smith (1998) proposed that multiple factors contribute to RQ.
The relationship between customer and company is positively
related to the strength of the mutual satisfaction and expectations
on both sides. Garbarino and Johnson (1999) pointed out that RQ
includes satisfaction, trust and commitment, aspects which positively influence customers’ future intentions.
2.4. Measurement of RQ
RQ is an important index for evaluating the strength of the relationship between the supplier and customer. Many researchers
agree that customer trust, satisfaction and commitment, are key
factors in evaluating RQ. For example, Crosby et al. (1990) and
Tam and Wong (2001) proposed that satisfaction and trust are
key aspects of RQ; Mohr and Spekman (1996), Morgan and Hunt
(1994), and Sanchez-Garcia et al. (2007) stated that trust and commitment are key factors in evaluating RQ. Chakrabarty et al. (2007),
Garbarino and Johnson (1999), Ivens (2004), Ndubisi (2006), and
Smith (1998) concluded that RQ is formed by satisfaction, trust and
commitment. Thus, this study integrates the three items above to
measure RQ. The following sections describe these factors in greater
detail.
“Trust” means that the customers believe sales personnel will
provide them with long-term benefit and service (Crosby et al.,
1990). Doney and Cannon (1997) pointed out that trust is the
reputation and level of caring exhibited by the opposite side as
recognized by the decision maker on the target to be trusted, and
includes objective reputation and psychological care. Garbarino
and Johnson (1999) thought that trust is customer confidence in
the quality and reliability of the service provided by the organization. Lee and Kim (1999) thought that trust is the level of confidence
and willingness in the mind of a consumer. That is, consumer trust
depends on the confidence and willingness to deal with a company,
and such willingness originates from the reliability, integrity and
honesty of the company (Moorman et al., 1993).
Customer “satisfaction” means the satisfaction of the customer
during or after the purchase of a product or service, interaction with
service personnel, and entire experience provided by the company
compared to other companies (Selnes, 1993). Westbrook (1980)
pointed out that satisfaction is a recognition and evaluation process in which customers compare their actual experience with their
previous expectations. If a product meets or exceeds these expectations, the customer feels satisfied. Bearden and Teel (1983) and
Oliver et al. (1997) thought that customer satisfaction means the
level of like or dislike after consumption, which is an attitude based
entirely on experience. Thus, the overall customer satisfaction is a
key determinant of RQ (Ndubisi, 2006).
Customers’ “commitment” is very important to maintaining a
relationship with the other side. Commitment to the relationship
on the part of both partners is a key factor to successful RQ in the
long run, and helps to enhance long-term benefits (Morgan and
Hunt, 1994). Moorman et al. (1993) and Goodman and Dion (2001)
thought that commitment occurs when one of the partners wants to
continue and reinforce the relationship. Anderson and Weitz (1991)
proposed that commitment includes the desire to develop a stable relationship, the willingness to make short term sacrifices for a
long-lasting relationship, and having confidence in the stability of
the relationship.
To ensure the content validity of the scales, the measurement
items were selected and modified from prior studies. The measures for Trust, Customer satisfaction and Customer commitment
264
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
are based on Sanchez-Garcia et al. (2007), Chakrabarty et al. (2007),
and Ndubisi (2006).
H1. When customers better recognize the CRM actions of a hotel,
they will view RQ more positively.
2.5. Customer Lifetime Value (CLV)
2.8. The relationship between RQ and CLV
Dwyer (1989) proposed that CLV is the net value of the expected
profit of the enterprise minus the related cost. Kotler (1997) pointed
out that CLV is the net profit obtained from a certain customer over
the lifetime of that customer, as s/he continues to purchase products from the company. Thus, CLV is the profit produced by all of
the steps that an enterprise takes to maintain a relationship with
the same customer (Levin, 1999).
Blatterg and Deighton (1996) pointed out that not all customers
are the same; as the competition in the market becomes more
severe, keeping valuable customers becomes more important to
enterprises. According to the 80/20 principle (Pareto Principle), 20%
of the customers bring the enterprise 80% of the profit (Berry, 1995).
Therefore, determining how to hold onto that 20% of the customers
and to how to measure their CLV are very important topics.
The final objective of CRM for the enterprise is to increase “Customer Lifetime Value.” Therefore, the effect of CRM is ultimately to
enhance CLV through RQ (Jackson, 1989). Pepper and Rogers (1993)
found that customers with high RQ will recommend a product
through word of mouth to relatives and friends. These customers
are more willing to re-purchase and also have higher loyalty. Moreover, customers with high loyalty will contribute to a company’s
profit over the long term and increase the sales and profits of the
company.
Crosby et al. (1990) pointed out that RQ influences customer
loyalty. Garbarino and Johnson (1999) found that RQ affects the
willingness of customers to either stay or leave in the future.
Keaveney (1995) also found that the RQ between the customer and
the enterprise is a key factor in the loyalty of a customer. Kumar
et al. (1995) thought that better RQ reduces the conflict between
the customer and the enterprise, enhances customer loyalty to the
enterprise, enhances customer willingness for continuing transactions, and increases customer usage quantity.
Leu and Hsieh (2000) found that RQ has a significant influence
on customer usage quantity, loyalty, product purchase intentions,
and word of mouth. These findings indicate that higher customer
satisfaction with RQ creates a positive effect on the customer’s view.
This in turn increases the company’s profit and improves CLV.
To summarize the findings above, a positive correlation exists
between RQ and CLV. This study measures CLV by usage quantity,
loyalty, word of mouth, and purchase intention, and proposes the
following hypotheses:
2.6. Measurement of CLV
CLV is the net value of the profit that an enterprise, over a certain
period of years, will earn from an average customer. CLV contains
the following four evaluation indexes: retention rate, annual sales,
direct cost, and interest rate (Hughes, 1994). Kim and Cha (2002)
measured CLV by customers’ shares of purchase, relationship continuity and word of mouth.
McDonald (1996) proposed that CLV can be evaluated by two
important aspects:
(1) Core relationship, which includes two items:
Usage factor: This is the duration and strength of the relationship between the company and the customer, that is,
the contact frequency or usage quantity of the customer.
Fan identification: This represents the customer’s personal
commitment and affection, such as loyalty.
(2) Extension relationship, which includes two items:
Product merchandising: This is the purchase intention as
affected by sales and communication tools.
Word of mouth: This measures the effect of the products
and services provided by the company based on the recommendations of existing customer to potential customers.
This study evaluates CLV based on the consumer’s perspective.
Therefore, usage quantity, loyalty, purchase intention, and word of
mouth serve as CLV measurement indices. The measurement items
for CLV were adapted from the study of Kim and Cha (2002), and
McDonald (1996).
2.7. The relationship between CRM and RQ
CRM can reduce consumers’ transaction cost or uncertainty,
which in turn enhances the relationship between the customer and
the enterprise. Crosby et al. (1990) proposed that CRM can enhance
RQ, an important factor in evaluating whether the relationship
between the enterprise and the customer is strong or weak, good
or bad (Kumar et al., 1995; Storbacka et al., 1994). Garbarino and
Johnson (1999) found that customers with a stronger relationship
to the enterprise have more positive recognition of the enterprise’s
CRM actions, and generally more positive views of RQ factors, such
as: degree of trust, satisfaction and commitment. Since trust, satisfaction and commitment are foundational to RQ (Garbarino and
Johnson, 1999), CRM clearly has a positive influence on RQ. Therefore, this study proposes the following hypotheses:
H2a.
RQ has a positive influence on the CLV “usage quantity.”
H2b.
RQ has a positive influence on CLV “loyalty.”
H2c.
RQ has a positive influence on CLV “word of mouth.”
H2d.
RQ has a positive influence on CLV “purchase intentions.”
2.9. Difference of hotel types
According to Tourism Bureau of the Ministry of Transportation
and Communications of Taiwan (2008), there were 90 tourism
hotels, 2613 general hotels, and 2519 guesthouses in Taiwan. A
tourism hotel is a leisure service business that provides lodging
and related leisure services to tourists. A general hotel has the primary business of providing lodging and rest services. A guesthouse
is operated through the use of a spare room in a private home, and is
often associated with locals, natural landscapes, ecology, environmental resources and agricultural, forestry, etc. Guesthouses are
usually operated as a family side business to provide rural-style
lodging to tourists.
In business operation aspects, tourism hotels, general hotels,
and guesthouses are very different. For example, guesthouses
emphasize a service charge that suits the public and self-assisted
service; the facility is not luxurious, but is filled with lots of special
features. Although the service may not be fancy, it offers lots of fun,
a rural nature, etc. It is often associated with local natural resources
and cultural features to provide unique lodging and dining service
(Taiwan Leisure Farming Development Association, 2004). General
hotels, on the other hand, do not emphasize cultural features, and
focus instead on providing convenient lodging services. Tourism
hotels, in addition to providing more professional service, provide
software and hardware which are better and of a higher class than
those provided by guesthouses and general hotels.
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
Customer Lifetime
Value (CLV)
Customer
Relationship
Management
(CRM)
H1
Relationship
Quality (RQ)
Satisfaction
Trust
Commitment
H2a
Usage Quantity
H2b
Loyalty
H2c
Word of Mouth
H2d
Purchase Intention
265
not clear, and these were revised or had examples given for better
description.
After correcting the questionnaire, convenience sampling was
again used to select 62 people for a sample pilot test. The data collected was then analyzed for reliability and validity. The results of
this pilot test indicated that Cronbach’s ˛ values of measurement
perspectives were all greater than 0.7. The factor loadings of all
questionnaire items were also greater than or close to 0.5, which
meets the standards of reliability and validity (Hair et al., 2006;
Nunnally, 1978). Hence, the resulting survey was used as the formal
questionnaire for a large-scale survey.
H3
Comparison of consumer groups with different preferences on hotel types
Fig. 1. Research framework.
To summarize the above, many differences exist among tourism
hotels, general hotels, and guesthouses. Their respective CRM
strategies also differ, and thus have different influences on RQ and
CLV. This study also explores if differences exist with customer
groups with different hotel preferences. Therefore, we measure
which type of hotel customers prefer when they travel in Taiwan,
and propose the following hypothesis:
H3. Consumer groups with different hotel preferences will exhibit
differences in the relationships among CRM, RQ, and CLV.
3. Research design
3.1. Research framework
To sum up the literature review and research hypothesis, this
study uses the research framework depicted in Fig. 1. A questionnaire design and sampling survey verify the research hypothesis.
This study investigates the correlation between CRM and RQ
formed by customers’ satisfaction, trust and commitment, and evaluates the influence of RQ on four CLV factors: usage quantity,
loyalty, word of mouth, and purchase intentions. In addition, this
study compares the effect of different hotel preferences on these
relationship models.
3.2. Questionnaire design
The initial draft of the measurement variables was first designed
according to the theory and literature reviewed above. Next, an indepth interview was performed on 30 consumers to collect views
and opinions regarding CRM, RQ and CLV held by consumers who
stayed at hotels or guesthouses in Taiwan. The main purpose of this
study was to understand consumer viewpoints and behavior and
use them as reference and a basis for designing the questionnaire.
After repeated discussions and corrections by a focus group of 8
researchers, the questionnaire was then generated in four parts:
hotel types, CRM, RQ, and CLV. The first section adopted a nominal
scale for evaluation; the other three sections used a Likert sevenpoint scale with a score of 1 to 7: the higher the score, the higher
the degree of agreement (see Table 1).
3.3. Pre-test and pilot
To acquire an effective measurement scale, two stages of pretest and pilot were used to correct the questionnaire before the
formal survey. For the pre-test, convenience sampling was used to
select 35 consumers who experienced staying at a hotel or guesthouse, and these 35 people were given in-depth interviews. The
results of these interviews revealed that some of the questions were
4. Research results and discussion
4.1. Sampling
This study selected Taiwanese consumers who stayed at their
preferred hotels or guesthouses during the past year as the main
research subjects. We collected the data by convenience sampling method at hotels and guesthouses, and sampled people.
The responders were asked to fill in a questionnaire about their
preferred hotels or guesthouses. We gathered data from 775
respondents via personal-interviews during two months, from
March 2009 to May 2009. After excluding 40 invalid questionnaires
and 47 questionnaires that could not be classified by lodging type,
the valid questionnaires totaled 688 copies, for an effective return
rate of 88.77%. The sample structure was then divided into two parts
based on personal background and consumption data for analysis
(as shown in Appendix A).
Personal background information shows that interviewees were
65.4% females and 34.6% males; 48.1% of them were aged 21–30
years old, 24.9% were aged 31–40, and 13.7% were aged 41–50;
27.6% of respondents were high school graduates and 63.4% had
college degrees; 24.3% were students, 10.3% worked in government,
7.8% worked in manufacturing, 14.7% worked in the commercial industry, and 32.7% worked in the service industry; many
(46.2%) earned an average personal monthly income of 750–1500
US dollars, followed by those who earned (40.3%) under 750 US
dollars. The backgrounds of responders included various characteristics, thus making the sample structure suitable. Beside, a survey
performed by Eastern Online (2005) indicates that the high consumption capability of single females aged 25–35 years old has
caught the attention of hotel enterprises. The chief economic advisor of Visa Card (Wong, 2007) pointed out that the consumption
power of Asian females is rising rapidly, and the main consumption target for these female consumers is leisure and entertainment
related to fashion, for example, the visit of spring SPA and tourism.
These phenomena agree with the characteristics of the sample in
this study, which can therefore be used to represent the consumption status of Taiwan’s hotel market.
The consumption data indicates that most consumers stayed at
hotels during recent one year and the average interval duration
of lodging in a hotel was more than two years. The average room
price ranged from 60 to 100 US dollars for a 2-person room. The
average lodging duration was 2 days, and the main lodging purpose
was leisure vacation. The only major difference is that the average
period of lodging in a general hotel was one day, which shows that
consumers prefer to stay at general hotels for shorter periods.
4.2. Reliability and validity analysis
This study uses exploratory factor analysis, Cronbach’s ˛, and
correlation coefficient to test the validity and reliability of valid
questionnaires. After reliability and validity testing, two CRM
items and two CLV items with factor loading lower than 0.5 were
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S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
Table 1
Measurement variables.
Measurement perspective
Items
References
Hotel types
• Which type of hotel you prefer to stay? (tourism hotel, general hotel, or
guesthouse)
Tourism Bureau of the Ministry
of Transportation (2008)
A1: The company has provided customized service.
A2: The company has a privacy protection policy.
A3: Searching for information about the company is easy.
A4: The company provides detailed maps and transportation guides.
A5: The service times of the company meet customer requirements.
A6: The company provides a convenient room reservation service.
A7: The company provides a convenient payment process.
A8: The company provides a convenient and easy to use facility.
A9: The company cares for customer’s need eagerly.
A10: The company replies to customer opinions.
• The company has a member program.a
A11: The company has a website.
A12: The company has convenient interactive communication channel.
• The company has questionnaire survey policy for customer.a
Ming and Chen (2002) and Keeney
(1999)
CRM
RQ
Satisfaction
Trust
Commitment
B1: The services provided by the company give us wonderful experience.
B2: The environment of the company satisfies me.
B3: The service attitude of company employees satisfies me.
B4: The professional knowledge of company employees satisfies me.
B5: The company met my expectations.
B6: The service provided by the company is trustworthy.
B7: The information provided by the company is accurate.
B8: The company will take customer’s benefit as the first priority.
B9: The company deals with customers honestly.
B10: The company is dependable.
B11: The company meets its commitments to customers.
B12: I would like to maintain a good relationship with the company.
B13: I care about the development of the company.
B14: I am happy to provide suggestions to the company for its products or
services.
B15: If the company sells a membership card or lodging ticket, I would like to
buy it.
Sanchez-Garcia et al. (2007);
Ndubisi (2006); Chakrabarty,
Whitten & Green (2007)
CLV
Usage quantity
Loyalty
Word of mouth
Purchase intention
a
• I come to the company for lodging almost every year.a
C1: I am willing to purchase from this company again.
C2: The money I spend here is well-spent.
C3: I would like to buy more from this company.
C4: I am a loyal customer of this company.
C5: I would still use the services of this company even if another company
offers me a promotional or favored price.
C6: Even if the price increases, I still would like to go to this company for
lodging.
C7: When I need travel or lodging, this company is my best choice.
• If I cannot shop in the company again, I would take it as a loss.a
C8: If someone asks me for information on a related product, I provide them
with information about this company.
C9: I would like to share my consumption experience from this company with
others.
C10: I would like to register as a member of the company and share my
opinions on its advantages.
C11: I would like to, through my introduction, let my relatives and friends
become loyal customer of this company.
C12: I will purchase this company’s product or service.
C13: I will repeat purchase this company’s product.
C14: I will consume a new product through the promotion from the service
personnel of the company.
C15: I hold positive attitude toward this company.
McDonald (1996); Kim and Cha
(2002).
Deleted item.
removed, and the analysis was performed again. Through factor analysis and the varimax method, the 14-items of CRM were
coalesced into one factor; RQ was further divided into three dimensions; and CLV was further divided into four dimensions in all
three types of hotels. The results meet the concepts of previous
researches (e.g. Chakrabarty et al., 2007; McDonald, 1996; Ndubisi,
2006). We tested every factor and dimension again (shown in
Table 2), and the results showed that Cronbach’s ˛ of each factor or dimension ranged from 0.827 to 0.951, which meets the
requirement of 0.7 or greater. This means that the reliability of each
measurement factor is high (Nunnally, 1978). The validity analysis results show that the eigenvalues of factors are greater than 1,
the cumulative explained variances are all greater than 0.5, factor
loadings of items are all greater than 0.5, and the correlation coefficients of item to total are all greater than 0.5, which means that
all of the measurement factors and dimensions have convergent
validity (Hair et al., 2006).
In addition, the question items were designed according to theory and literature, and examined and corrected by experts. Finally,
they were tested by pre-test, pilot and focus groups to confirm the
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
Table 2
Reliability and validity analysis.
Perspectives
267
A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12
Tourism hotel
Cronbach’s ˛
Eigenvalue
Cumulative explained
variance (%)
CRM
6.971
58.096
0.933
RQ
Satisfaction
Trust
Commitment
3.781
4.244
2.967
75.623
70.727
74.170
0.918
0.916
0.879
CLV
Usage quantity
Loyalty
Word of mouth
Purchase intention
2.403
2.672
2.928
3.039
80.114
66.798
73.198
75.987
0.874
0.827
0.875
0.895
Perspectives
General hotel
B1
B2
B3
B4
B5
B12
B13
B14
B15
Customer Relationship
Management
Satisfaction
B6
B7
B8
B9
B10
B11
Relationship
Quality
Trust
Commitment
Usage Quantity
Loyalty
Word of
Mouth
Purchase Intention
Cronbach’s ˛
Eigenvalue
Cumulative explained
variance (%)
CRM
7.400
61.665
0.942
RQ
Satisfaction
Trust
Commitment
3.989
4.669
2.904
79.784
77.811
72.611
0.936
0.943
0.870
CLV
Usage quantity
Loyalty
Word of mouth
Purchase intention
2.467
2.820
3.015
3.101
82.244
70.506
75.366
77.528
0.891
0.860
0.885
0.903
Perspectives
Guesthouse
C1 C2 C3
C4 C5 C6 C7
C8 C9 C10 C11
C12 C13C14C15
Fig. 2. Relationship model.
Eigenvalue
Cumulative explained
variance (%)
Cronbach’s ˛
CRM
7.116
59.301
0.935
RQ
Satisfaction
Trust
Commitment
4.047
4.824
2.927
80.947
80.408
73.164
0.941
0.951
0.875
CLV
Usage quantity
Loyalty
Word of mouth
Purchase intention
2.325
3.114
3.254
3.113
77.512
77.860
81.340
77.836
0.854
0.903
0.920
0.903
content of the formal questionnaire. Therefore, we are confident
that these measurement scales have content validity. Furthermore,
this study uses the theory and empirical cases presented by previous scholars and experts as references for constructing the research
structure and measurement scales. Hence, the research framework
and measurement scale possess nomological validity.
4.3. Interactive relationship analysis
This study uses Structural Equation Modeling (SEM) to test the
interrelated dependence relationships among multiple variables.
Meanwhile, the fitness of a model is judged by the rules of an excellent model’s ratio of chi-square value to degree of freedom (2 /df)
which should not be larger than 3 (Carmines and MacIver, 1981);
the RMR should be smaller than 0.08 and RMSEA should be smaller
than 0.05, and GFI, AGFI, NFI, RFI, and CFI should be larger than 0.9
(Bagozzi and Yi, 1988; Joreskog and Sorbom, 1989). Fig. 2 shows
the relationship model in this study.
For the three consumer groups of different hotel preferences,
this study performs SEM analysis on three relationship models. The
results show that the model fitness for all three models reach or
come close to the target value. Therefore, the three relationship
models of different hotel types are acceptable, as Table 3 shows. In
addition, the results in Tables 4–6 all show that significant and positive relationship exists between measurement indicators and their
latent variables, which means that the three relationship models of
different hotel types are effective.
SEM analysis reveals that the relationship paths of the three
models of different hotel types are the same. The results in Table 7
show that a significant and positive relationship exists between
CRM and RQ, which means that CRM has a strong and positive
influence on RQ. When customers have more appreciation for the
Table 3
Fitness of relationship models of different preference groups.
Model fit criteria
Tourism hotel
(221)
General hotel
(266)
Guesthouse
(201)
2
df
2 /df
P value
RMR
GFI
AGFI
NFI
RFI
CFI
RMSEA
1402.550
734
1.911
0.000
0.079
0.776
0.725
0.844
0.817
0.918
0.064
1419.108
734
1.933
0.000
0.086
0.803
0.758
0.883
0.862
0.939
0.059
1400.408
734
1.908
0.000
0.099
0.757
0.702
0.859
0.835
0.927
0.067
Table 4
Estimates of regression weight for measurement indicators of CRM.
Measurement indicators
CRM → A1
CRM → A2
CRM → A3
CRM → A4
CRM → A5
CRM → A6
CRM → A7
CRM → A8
CRM → A9
CRM → A10
CRM → A11
CRM → A12
***
P < 0.001.
Estimates of regression weight
Tourism
hotel (221)
General
hotel (266)
Guesthouse
(201)
0.701***
0.702***
0.763***
0.736***
0.774***
0.732***
0.745***
0.790***
0.732***
0.692***
0.641***
0.715***
0.775***
0.747***
0.730***
0.743***
0.788***
0.765***
0.807***
0.798***
0.713***
0.706***
0.654***
0.776***
0.753***
0.711***
0.676***
0.706***
0.783***
0.781***
0.775***
0.759***
0.740***
0.719***
0.599***
0.773***
268
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
Table 5
Estimates of regression weight for measurement indicators of RQ.
Measurement indicators
RQ → satisfaction
RQ → trust
RQ → commitment
Satisfaction → B1
Satisfaction → B2
Satisfaction → B3
Satisfaction → B4
Satisfaction → B5
Trust → B6
Trust → B7
Trust → B8
Trust → B9
Trust → B10
Trust → B11
Commitment → B12
Commitment → B13
Commitment → B14
Commitment → B15
***
results of all three models show that the better the RQ, the higher
the usage quantity. These results support H2a and agree with the
research of Kumar et al. (1995). Furthermore, a positive and significant correlation exists between RQ and loyalty, which means that
the better the RQ, the higher the customer loyalty. This finding supports H2b and agrees with the research results of Keaveney (1995).
RQ and word of mouth are also significantly and positively correlated, meaning the better the RQ, the better the word of mouth.
These results support H2c and agree with Pepper and Rogers (1993).
Finally, RQ has a significant and positive influence on consumer
purchase intentions, which means that the better the RQ, the better the purchase intentions. This supports H2d and agrees with the
research of Leu and Hsieh (2000).
Estimates of regression weight
Tourism
hotel (221)
General
hotel (266)
Guesthouse
(201)
0.964***
0.976***
0.754***
0.860***
0.780***
0.891***
0.867***
0.836***
0.852***
0.822***
0.780***
0.840***
0.769***
0.794***
0.984***
0.863***
0.882***
0.664***
0.972***
0.972***
0.836***
0.896***
0.816***
0.897***
0.899***
0.836***
0.878***
0.879***
0.849***
0.878***
0.814***
0.849***
0.926***
0.845***
0.857***
0.669***
0.994***
0.985***
0.834***
0.931***
0.856***
0.885***
0.878***
0.838***
0.899***
0.864***
0.853***
0.866***
0.848***
0.879***
0.948***
0.862***
0.861***
0.688***
4.4. Comparison of relationship models
This study uses multi-group analysis of competing models to
compare the relationship models of different hotel preference
groups (tourism hotels, general hotels, and guesthouses). The main
objective of this analysis is to find any differences in different preference groups in the relationships among CRM, RQ, and CLV. The
fitness indexes of the competing model all meet or come close to
their target values, indicating that this competing model is acceptable (as Table 7 indicates).
The comparison results show that although the three models
have the same relationship structures, the relationship strength of
some paths differs. The following section provides detailed discussion of the results of comparing the standardized parameter
estimation values of the three relationship models (as in Table 7):
P < 0.001.
Table 6
Estimates of regression weight for measurement indicators of CLV.
Measurement indicators
Usage quantity → C1
Usage quantity → C2
Usage quantity → C3
Loyalty → C4
Loyalty → C5
Loyalty → C6
Loyalty → C7
Word of mouth → C8
Word of mouth → C9
Word of mouth → C10
Word of mouth → C11
Purchase intention → C12
Purchase intention → C13
Purchase intention → C14
Purchase intention → C15
***
Estimates of regression weight
Tourism
hotel (221)
General
hotel (266)
Guesthouse
(201)
0.782***
0.843***
0.856***
0.781***
0.801***
0.733***
0.772***
0.851***
0.597***
0.837***
0.893***
0.823***
0.805***
0.868***
0.862***
0.816***
0.888***
0.867***
0.788***
0.849***
0.901***
0.806***
0.844***
0.601***
0.832***
0.926***
0.866***
0.808***
0.839***
0.927***
0.774***
0.813***
0.863***
0.863***
0.865***
0.897***
0.887***
0.861***
0.627***
0.849***
0.929***
0.800***
0.792***
0.863***
0.966***
(1) In the influence of CRM on RQ, the T-test results show that the
three models do not show significant differences. This means
that no significant difference exists in the strength of the influence of CRM on RQ for all three groups, that is, all paths exhibits
a positive and strong relationship.
(2) In the influence of RQ on CLV “usage quantity,” the three models
all show a strong path relationship. However, the T-test results
indicate that a significant difference exists between consumers
who prefer tourism hotels and those who prefer guesthouses
(t = 2.170). A significant difference also exists between consumers who prefer tourism hotels and those who prefer general
hotels (t = 1.824). Results show that consumers who prefer
guesthouses or general hotels feel that RQ will have greater
influence on usage quantity than do consumers who prefer
tourism hotels. All these results show that tourism hotels have
a lower strength on this path relationship.
(3) Consumers with different hotel preferences all show a strong
relationship in the influence of RQ on “loyalty” of CLV. However,
P < 0.001.
CRM actions offered by a hotel, then the RQ is better. These results
support H1 and agree with the research of Garbarino and Johnson
(1999).
The relationship analysis of RQ and CLV shows that the RQ has
a significant positive influence on consumers’ usage quantity. The
Table 7
The comparison between different preference groups.
Relationship path
Standardized parameter estimates
CRM → RQ
RQ → usage quantity
RQ → loyalty
RQ → word of mouth
RQ → purchase intention
2
df
Fitness of competing model
4317.911
2268
*
**
***
P < 0.05.
P < 0.01.
P < 0.001.
T-test
Tourism hotel
General hotel
Guesthouse
Tourism hotel vs.
general hotel
Tourism hotel vs.
guesthouse
General hotel vs.
guesthouse
0.873***
0.697***
0.638***
0.632***
0.710***
0.911***
0.825***
0.829***
0.837***
0.853***
0.916***
0.873***
0.813***
0.821***
0.884***
0.977
1.824*
2.59***
2.705***
1.509
1.521
2.170**
2.732***
2.617***
2.306**
0.685
0.541
0.452
0.119
1.302
2 /df
P value
RMR
GFI
AGFI
NFI
RFI
CFI
RMSEA
1.904
0.000
0.099
0.777
0.733
0.861
0.841
0.928
0.036
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
the T-test results show that a significant difference (t = 2.732)
exists between consumers who prefer tourism hotels and those
who prefer guesthouses. A significant difference (t = 2.59) also
exists between consumers who prefer tourism hotels and those
who prefer general hotels. This means that consumers who
prefer either guesthouses or general hotels feel that RQ has a
greater influence on loyalty than do those who prefer tourism
hotels. These results show that tourism hotels have the lowest
strength in this relationship path.
(4) In the influence of RQ on CLV “word of mouth”, T-test results
show that a significant difference (t = 2.705) exists between
consumers who prefer tourism hotels and those who prefer
general hotels. Moreover, a significant difference (t = 2.617)
exists between consumers who prefer tourism hotels and those
who prefer guesthouses. These results also show that tourism
hotels have the lowest strength in this relationship path.
(5) Finally, in the influence of RQ on CLV “purchase intentions”, Ttest results show that a significant difference (t = 2.306) exists
between consumers who prefer tourism hotels and those who
prefer guesthouses. This means that the effect of RQ on purchase
intentions is greater for consumers who prefer guesthouses
than for those who prefer tourism hotels.
To summarize the findings above, consumer groups with different hotel preferences exhibit slight significant differences in the
strength of the relationships between CRM, RQ and CLV. This result
provides partial support for H3. However, there is no significant
difference between consumers who prefer general hotels and those
who prefer guesthouses. Research results show that a CRM strategy
has a significantly lower effect on tourism hotels than on general
hotels or guesthouses.
5. Conclusions and suggestions
5.1. Conclusions and discussion
This study investigates the consumer views on CRM, RQ and
CLV for three kinds of hotels: tourism hotels, general hotels, and
guesthouses, and the differences in these relationships based on
hotel type. This study develops an effective measurement scale and
relationship model, and provides the following conclusions.
5.1.1. The effect of CRM
The results of this study show that when customers show higher
awareness on the CRM actions of the hotel, the recognized RQ will
be better; meanwhile, the better the RQ, the higher the four dimensions of CLV, individually. This result suggests that all kinds of hotels
should emphasize CRM actions based on cost/benefit concept since
the effects of CLV on usage quantity, loyalty, word of mouth, and
consumer’s purchase intentions all can be enhanced by maintaining RQ between enterprise and customer. Meanwhile, the effect of
RQ can be enhanced by implementing CRM.
5.1.2. Comparison of consumer groups with different hotel
preferences
Study results and a comparison between consumer groups show
that no significant difference exists in the relationship strength for
the influence of CRM on RQ for the three hotel preference groups.
All three groups exhibit positive strong relationships. However, the
general hotel group has more recognition of the effect of RQ on
the three dimensions of CLV (usage quantity, loyalty and word of
mouth) than the tourism hotel group does. In addition, focusing on
the influence of RQ on the all four dimensions of CLV, consumers
who prefer guesthouses show a higher recognition of the influence
of RQ on CLV than do consumers who prefer tourism hotels. This
269
implies that hotel type is an important interference factor. Consumers with different hotel preferences do indeed have different
views of RQ and its effects on CLV. This result can be used as a
reference by different hotels in preparing their CRM strategies.
5.2. Managerial implications
This study shows that when a hotel implements CRM activities,
it will indeed positively affect RQ and further enhance customer
usage quantity, loyalty, word of mouth, and purchase intention.
Moreover, comparative analysis shows that consumers with different hotel preferences exhibit significant differences in some
relationship paths.
Consumers with a preference for general hotels exhibit a
stronger RQ influence on loyalty and RQ influence on word of
mouth. Thus, customer loyalty and word of mouth will be competitive advantages for general-type hotels. Therefore, general
hotels should focus on providing convenient lodging services and
a wonderful experience to customers for increased loyalty, such
as offering a clean environment, convenient service process, and
professional employees to satisfy customers’ expectations.
On the other hand, consumers with a preference for guesthouses show a stronger CRM influence on RQ, RQ influence on
usage quantity, and RQ influence on purchase intentions. Therefore,
guesthouses should maintain their CRM and RQ efforts to enhance
consumer usage quantity and purchase intentions, such as maintaining an association with local resources and culture to provide
a unique service, as well as providing detailed maps, transportation guides, convenient room reservation service, and an interactive
communication channel.
Consumers with a preference for tourist hotels exhibit a weaker
relationship between RQ and CLV. Thus, besides improving CRM
activities to enhance its RQ with consumers and reinforce the
effects of CLV, tourist hotels should provide more professional
service and new facilities to attract new consumers and spur
repeat business by loyal customers. Since the professional service, innovative software and hardware facilities are the core
competitive advantage of tourism hotels, tourism hotels should
provide customized service, provide information searching system
and website to reply to customers’ opinions and queries, provide
an innovative and useful facility, and perform surveys to understand customers’ needs (Taiwan Leisure Farming Development
Association, 2004).
Because previous studies perform fewer comparisons of
consumer groups of different hotel preferences on the CRM relationship model, the analysis result of this study, can not only
construct the related influential factors and concept framework,
but also provide references to different hotel enterprises to prepare
CRM strategy and enhance efficiency. Thus, this study possesses
both academic value and practical contributions.
5.3. Limitations and future research
Since different types of hotels will conduct different CRM activities, this study might not be able to introduce all the CRM actions
of all types of hotels. Subsequent studies can set up more suitable
variables by surveying more multi-element literature or conducting enterprise surveys to further analyze the differences of CRM
effectiveness between different CRM actions.
Since previous studies showed that RQ (which aggregate
customers’ satisfaction, trust, and commitment) had a positive relationship with repeat purchase, usage quantity, loyalty, and word
of mouth (Kim et al., 2001; Kim and Cha, 2002), we therefore
aggregate the three dimensions of RQ to explore the influence of
RQ on the four dimensions of CLV. Furthermore, future research
should measure the individual dimensions of RQ and explore the
270
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
relationship between CRM and the three dimensions of RQ, and
the relationships among the three dimensions of RQ and the four
dimensions of CLV individually.
This study takes the customer’s viewpoint to investigate customer perceptions of CRM, RQ and CLV. The results provide some
important information about CRM, RQ and CLV from customers for
enterprises. However, management and customers may not have
the same definitions of the three constructs. Therefore, the perception differences between management and customers should be
the subject of further research.
This study surveyed domestic travelers only. Therefore, the findings can lead to further research in other countries for generalizing
to the general public.
Moreover, different target groups or industry types may generate different research results. Future research should investigate
other industries, for example, restaurants or the travel industry.
Hopefully, such studies will confirm the practicality of the conceptual framework in this study.
Appendix A. The demographic and consumption data
Category
Items
Tourism hotel
General hotel
Guesthouse
Total
Gender
Male
Female
87(39.4%)
134(60.6%)
92(34.6%)
174(65.4%)
59(29.4%)
142(70.6%)
238(34.6%)
450(65.4%)
Age
Under 21
21–30
31–40
41–50
More than 50
15(6.8%)
86(38.9%)
65(29.4%)
39(17.6%)
16(7.2%)
28(10.5%)
128(48.1%)
59(22.2%)
37(13.9%)
14(5.3%)
13(6.5%)
117(58.2%)
47(23.4%)
18(9.0%)
6(3.0%)
56(8.1%)
331(48.1%)
171(24.9%)
94(13.7%)
36(5.2%)
Education
Junior high school
Senior high school
College
Graduate school
11(5.0%)
50(22.6%)
138(62.4%)
22(10.0%)
15(5.6%)
68(25.6%)
161(60.5%)
22(8.3%)
7(3.5%)
39(19.4%)
137(68.2%)
18(9.0%)
33(4.8%)
157(22.8%)
436(63.4%)
65(9.0%)
Background or occupation
Student
Worked in government
Worked in manufactory
Worked in commercial
Worked in service industry
The others
43(19.5%)
27(12.2%)
14(6.3%)
43(19.5%)
67(30.3%)
27(12.2%)
75(28.2%)
31(11.7%)
19(7.1%)
34(12.8%)
89(33.5%)
18(6.8%)
49(24.4%)
13(6.5%)
21(10.4%)
24(11.9%)
69(34.3%)
25(12.4%)
167(24.3%)
71(10.3%)
54(7.8%)
101(14.7%)
225(32.7%)
70(10.2%)
Personal monthly income (US $)
Under 750
750–1500
1501–2250
More than 2250
70(31.7%)
101(45.7%)
32(14.5%)
18(8.1%)
122(45.9%)
115(43.2%)
21(7.9%)
8(3.0%)
85(42.3%)
102(50.7%)
7(3.5%)
7(3.5%)
277(40.3%)
318(46.2%)
60(8.7%)
33(4.8%)
Stayed at preferred hotel during recent time
One year ago
Nine months ago
A half year ago
Three months ago
One month ago
111(50.2%)
31(14.0%)
40(18.1%)
21(9.5%)
18(8.1%)
134(50.3%)
39(14.7%)
50(18.8%)
14(5.3%)
29(10.9%)
83(41.3%)
45(22.4%)
49(24.4%)
11(5.5%)
13(6.5%)
328(47.7%)
115(16.7%)
139(20.2%)
46(6.7%)
60(8.7%)
The average interval duration of lodging in a hotel
More than two years
Two years
One year
A half year
Three months or below
120(54.3%)
30(13.6%)
43(19.5%)
22(10.0%)
6(2.8%)
160(60.2%)
23(8.6%)
56(21.0%)
21(7.9%)
6(2.2%)
118(58.7%)
22(10.9%)
38(18.9%)
15(7.5%)
8(4.0%)
398(57.8%)
75(10.9%)
137(19.9%)
58(8.4%)
20(2.9%)
Types of preferred room
2-Person room
4-Person room
6-Person room
138(62.4%)
76(34.4%)
7(3.2%)
134(50.4%)
111(41.7%)
21(7.9%)
105(52.2%)
75(37.3%)
21(10.4%)
377(54.8%)
262(38.1%)
49(7.1%)
Expense per room (US $)
Under 60
60–100
101–160
More than 160
26(11.8%)
93(42.1%)
46(20.8%)
56(25.3%)
90(33.8%)
123(46.2%)
19(7.1%)
34(12.8%)
70(34.9%)
109(54.2%)
11(5.5%)
11(5.5%)
186(27.0%)
325(47.3%)
76(11.1%)
101(14.7%)
The average duration of lodging in a hotel once time
One day
Two days
Three days
More than three days
91(41.2%)
104(47.1%)
11(5.0%)
15(6.8%)
141(53.0%)
109(41.0%)
9(3.4%)
7(2.6%)
77(38.3%)
105(52.2%)
15(7.5%)
4(2.0%)
309(44.9%)
318(46.2%)
35(5.1%)
26(3.8%)
S.-I. Wu, P.-C. Li / International Journal of Hospitality Management 30 (2011) 262–271
References
Anderson, E., Weitz, B., 1991. The use of pledges to build and sustain commitment in distribution channels. Journal of Marketing Research 29 (February),
18–34.
Bagozzi, R.P., Yi, Y., 1988. On the evaluation of structural equation models. Journal
of Academy of Marketing Science 16 (1), 74–94.
Bearden, W.O., Teel, J.E., 1983. Selected determinants of consumer satisfaction and
complaint reports. Journal of Marketing Research 20 (February), 21–28.
Berry, L.L., 1995. Relationship marketing of services growing interest, emerging
perspectives. Journal of the Academy of Marketing Science 23 (4), 236–245.
Blatterg, R.C., Deighton, J., 1996. Manage marketing by the customer equity test.
Harvard Business Review 74 (July–August), 136–144.
Carmines, E., MacIver, J., 1981. Analyzing models with unobserved variables: analysis of covariance structures. In: Bohrnstedt, G., Borgatta, E. (Eds.), Social
Measurement: Current Issues. Sage, Beverly Hills.
Chakrabarty, S., Whitten, D., Green, K., 2007. Understanding service quality and relationship quality in is outsourcing. Journal of Computer Information Systems 48
(2), 1–15.
Christy, R., Gordon, O., Joe, P., 1996. Relationship marketing in consumer markets.
Journal of Marketing Management 12 (1–3), 175–187.
Crosby, L.A., Evans, K.R., Cowles, D., 1990. Relationship quality in services selling: an
interpersonal influence perspective. Journal of Marketing 54 (3), 68–82.
Doney, P.M., Cannon, J.P., 1997. An examination of the nature of trust in buyer–seller
relationships. Journal of Marketing 61 (April), 35–51.
Dwyer, F.R., 1989. Customer lifetime valuation to support marketing decision making. Journal of Direct Marketing 3 (4), 8–15.
Eastern Online Professional Lifestyle and Consumer Market Research Consultant,
2005. Web Site: http://www.isurvey.com.tw/, Date: 2008/10/16.
Garbarino, E., Johnson, M.S., 1999. The different roles of satisfaction, trust, and commitment in customer relationships. Journal of Marketing 63 (April), 70–87.
Goodman, L.E., Dion, P.A., 2001. The determinants of commitment in the distributormanufacturer relationship. Industrial Marketing Management 30 (3), 287–
300.
Gummsson, E., 1987. The new marketing-developing long-term interactive relationships. Long Range Planning 20 (4), 10–20.
Hair, J.F., Black, B., Babin, B., Anderson, R.E., Tatham, R.L., 2006. Multivariate Data
Analysis, 6th ed. Prentice Hall, New Jersey.
Hennig-Thurau, T., Klee, A., 1997. The role of dependence balancing in safeguarding
transaction-specific assets in conventional channels: a critical reassessment and
model development. Psychology and Marketing 14 (8), 737–764.
Hughes, A.M., 1994. Strategic Database Marketing. Probus Publishing Company,
Chicago.
Ivens, B.S., 2004. How relevant are different forms of relational behavior? An empirical test based on Macneil’s exchange framework. The Journal of Business and
Industrial Marketing 19 (5), 300–309.
Jackson, D., 1989. Determine a customer’s life time value. Direct Marketing, March,
60–62, May, 24–32, August, 28–30.
Jae, W.K., Jiho, C., William, Q., Jinsoo, P., 2004. The impact of CRM on firm- and
relationship-level performance in distribution networks. Communications of
the Association for Information System 14 (30), 632–652.
Joreskog, K.G., Sorbom, D., 1989. Lisrel 7: A Guide to the Program and Application,
2nd ed. SPSS Publications, Chicago.
Kandell, J., 2000. CRM, ERM, one-to-one decoding relationship management theory
and technology. Trusts & Estates 139 (4), 49–53.
Keaveney, S.M., 1995. Customer switching behavior in service industries: an
exploratory article. Journal of Marketing 59 (2), 71–82.
Keeney, R.L., 1999. The value of Internet commerce to the customer. Management
Science 45 (4), 533–542.
Khirallah, K., 1999. Should retail banks race toward the one-to-one future? Bank
Technology News 12 (4), 41–43.
Kim, W.G., Han, J.S., Lee, E., 2001. Effects of relationship marketing on repeat purchase and word of mouth. Journal of Hospitality & Tourism Research 25 (3),
272–288.
271
Kim, W.G., Cha, Y., 2002. Antecedents and consequences of relationship quality in
hotel industry. Hospitality Management 21 (4), 321–338.
Kotler, P., 1997. Marketing Management—Analysis Planning, Implementation, and
Control, 9th ed. Prentice-Hall, Englewood Cliffs, N.J.
Kumar, N., Scheer, L.K., Steenkamp, J.B., 1995. The effects of supplier fairness on
vulnerable resellers. Journal of Marketing Research 32 (1), 54–65.
Lee, J.N., Kim, Y.G., 1999. Effect of partnership quality on IS outsourcing success:
conceptual framework and empirical validation. Journal of Management Information Systems 15 (4), 29–61.
Leu, H.D., Hsieh, I.W., 2000. Relationships among customer satisfaction, brand equity
and customer lifetime value. Chung Yuan Journal 28 (2), 31–41.
Levin, A., 1999. Relationship management critical to web success. DM Review 3, 2–4.
Linoff, G.S., 1999. CRM: aka, the intelligent enterprise? Intelligent Enterprise 16
(November), 8–13.
Liu, Y.A., Chen, R.F., Chen, H.B., Wan, C.S., 2007. Customer relationship management
in the travel web site. Journal of Sport and Recreation Research 2 (2), 1–25.
McDonald, M., 1996. Service Quality and Customer Lifetime Value in Professional
Sport Franchises. University of Massachusetts.
Ming, V., Chen, J.M., 2002. Building a value measurement model for CRM system—an
empirical study based on quality function development. Soochow Journal of
Economics and Business 39 (December), 1–36.
Mohr, J.J., Spekman, R.E., 1996. Perfecting partnerships. Marketing Management 4
(4), 34–43.
Moorman, C., Deshpande, R., Zaltman, G., 1993. Factors affecting trust in market
research relationships. Journal of Marketing 57 (1), 81–101.
Morgan, R.M., Hunt, S.D., 1994. The commitment–trust theory of relationship marketing. Journal of Marketing 58 (3), 20–38.
Ndubisi, N.O., 2006. A structural equation modeling of the antecedents of relationship quality in the Malaysia banking sector. Journal of Financial Services
Marketing 11 (2), 131–141.
Nunnally, J.C., 1978. Psychometric Theory. McGraw-Hill, New York.
Oliver, R.L., Rust, R.T., Varki, S., 1997. Customer delight: foundations, findings and
managerial insight. Journal of Retailing 73 (3), 311–336.
Pepper, D., Rogers, M., 1993. The One to One Future: Building Relationships One
Customer at a Time. Doubleday, New York.
Rosenberg, L.J., Czepiel, J.A., 1984. A marketing approach for customer retention.
Journal of Consumer Marketing 1 (2), 45–51.
Sanchez-Garcia, J., Moliner-Tena, M.A., Callarisa-Fiol, L., Rodriguez-Artola, R.M.,
2007. Relationship quality of an establishment and perceived value of a purchase. The Service Industries Journal 27 (2), 151–174.
Selnes, F., 1993. An examination of the effect of product performance on brand
reputation, satisfaction and loyalty. European Journal of Marketing 27 (9),
19–35.
Smith, J.B., 1998. Buyer-seller relationships: similarity, relationship management,
and quality. Psychology & Marketing 15 (1), 3–21.
Spengler, B., 1999. Application status investigation of the 1999 Customer Relationship Management for Taiwan’s enterprises in 1999. eBusiness Executive Report
3, 9–15.
Storbacka, K., Standvik, T., Gronroos, C., 1994. Managing customer relationships for
profit: the dynamism of relationship quality. International Journal of Service
Industry Management 5 (6), 21–38.
Swift, R.S., 2001. Accelerating Customer Relationship: Using CRM and Relationship
Technology. Prentice Hall, New Jersey.
Taiwan Leisure Farming Development Association, 2004. Web Site: http://www.
taiwan-farming.org.tw/FarmingSocietywebsite/index.htm, Date: 2008/10/16.
Tam, J.L.M., Wong, Y.H., 2001. Interactive selling: a dynamic framework for services.
Journal of Services Marketing 15 (5), 379–396.
Tourism Bureau, M.O.T.C. Republic of Chain (Taiwan). Web Site: http://
admin.taiwan.net.tw/index.htm, Date: 2008/9/27.
Westbrook, R.A., 1980. Intrapersonal affective influences on consumer satisfaction
with products. Journal of Consumer Research 7 (1), 49–55.
Wong, Y.H., 2007. Holding Up Half of the Sky: The New Women Consumers of Asia,
1st ed. Wealth Magazine, Taiwan.