The Effects of Service Quality on Repurchase Intentions in Chinese Tourism Môn Kinh doanh quốc tế | Trường Đại học Công nghiệp Thành phố Hồ Chí Minh
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Tourism Management 52 (2016) 82e95
The effects of perceived service quality on repurchase intentions and
subjective well-being of Chinese tourists: The mediating role of relationship quality
Lujun Su a, Scott R. Swanson b, *, Xiaohong Chen a
a Business School Central South University, Collaborative Innovation Center of Resource-conserving & Environment-friendly Society and Ecological
Civilization, 932 Lushan South Street, Changsha Hunan, China
b Management and Marketing Department, University of Wisconsin-Eau Claire, Eau Claire WI 54701, USA H I G H L I G H T S
● We propose and test an integrated model with domestic Chinese hotel guests.
● Satisfaction fully mediates antecedent and outcome relationships.
● Identification partially mediates antecedent and outcome relationships.
● Hospitality firms can help satisfy self-definitional needs.
● Identification provides positive consequences. A R T I C L E I N F O A B S T R A C T Article history:
The current study provides and tests an integrated model that examines two relationship quality con- Received 5 June 2014
structs (overall customer satisfaction, customer-company identification) as mediating variables between Received in revised form
Chinese tourists' lodging service quality perceptions and two outcomes (repurchase intentions, subjec- 6 June 2015 Accepted 16 June 2015
tive well-being). The results of a study with domestic Chinese hotel guests (n ¼ 451) provide support for the proposed model. Speci Available online xxx
fically, the results indicate that overall customer satisfaction fully mediates the
relationship between perceived service quality and repurchase intentions and subjective well-being,
respectively. Customer-company identification partially mediates the relationship between perceived Keywords:
service quality and repurchase intentions and subjective wellbeing, respectively. We provide empirical Service quality Customer satisfaction
validation that customers do, indeed, identify with hospitality providers, and this, in-turn, provides Customer-company identi
positive consequences for both the service provider (i.e., repurchase intentions) and the customer (i.e., fication Repurchase intentions
subjective well-being). Managerial implications are provided, limitations noted, and future research Subjective well-being directions suggested.
© 2015 Elsevier Ltd. All rights reserved. 1. Introduction
more of their defecting customer base. The improved financial re-
wards are accrued through reduced customer acquisition market-
Customer relationships, and relationship marketing in partic-
ing costs, acquisition of new customers via positive word-of-
ular, have received considerable attention from both academicians
mouth, and larger purchases over time by less price-sensitive
and practitioners. Relationship marketing aims to build long-term,
loyal customers (Smit, Bronner, & Tolboom, 2007). Building
trusting, mutually beneficial relationships with valued customers
committed customer relationships “is increasingly emerging as a
(Kim & Cha, 2002). According to Reichheld and Sasser (1990),
strategy for organizations that strive to retain loyal and satisfied
companies can increase profits by almost 100% by retaining just 5%
customers in today's highly competitive environment” (Meng & Elliott, 2008, p. 509).
A social identity perspective can be useful to help establish the * Corresponding author.
relationship between companies and customers (Bhattacharya &
E-mail addresses: sulujunslj@163.com (L. Su), swansosr@uwec.edu
Sen, 2003). As such, customer-company identification is a
(S.R. Swanson), csu_cxh@163.com (X. Chen).
http://dx.doi.org/10.1016/j.tourman.2015.06.012
0261-5177/© 2015 Elsevier Ltd. All rights reserved. /
potentially useful construct for better understanding customer re-
research in tourism/hospitality has not examined the potential
lationships, yet there have been few studies that examine it in this
mediating role of customer-company identification as a relational
way (Ahearne, Bhattacharya, & Gruen, 2005). In addition, few construct.
studies pay attention to social identification antecedents (e.g.,
Third, this study not only examines customer repurchase in-
identification) to customer behaviors and have not yet incorporated
tentions as an economic outcome, it also proposes and investigates
them into established frameworks (He, Li, & Harris, 2012; Martínez
customer subjective well-being as a social outcome of service
& Rodriguez del Bosque, 2013). Ahearne et al. (2005) point out that
evaluation perceptions. This study extends previous service-based
customer-company identification may have a greater effect when
relationship marketing studies by broadening the traditional
the offering is intangible, as in the case of services. Thus, it may be
research perspective that focuses only on economic outcomes.
worthwhile to examine customer-company identification in a
Although the study of subjective well-being has received increased hospitality services context.
attention among tourism researchers (e.g., Dolnicar et al., 2012;
Hotels can provide a wide range of tourist services such as ac-
Gilbert & Abdullah, 2004; Neal, Sirgy, & Uysal, 1999; Neal et al.,
commodation, food service, entertainment, local transportation,
2007; Sirgy, Kruger, Lee, & Yu, 2011), few studies have yet to
site recommendations, and arrangements for local tours. Thus, the
explore the antecedents and mechanism of tourists' subjective
hotel service experience is an important component of the entire
well-being. This study proposes perceived service quality, as an
tourism experience that, in some circumstances, may be reflective
antecedent of customer subjective well-being, and relational
of the overall tourism industry.
quality (i.e., overall customer satisfaction, customer-company
Leisure activities, including tourism, and their importance to life
identification) as both antecedents to customer subjective well-
satisfaction and a sense of well-being have been previously noted in
being and mediators of perceived service quality.
the tourism/leisure literature (e.g., Diener & Suh, 1997; Dolnicar,
In the following sections, we first utilize prior literature to
Yanamandram, & Cliff, 2012; Hobson & Dietrich, 1994; Karnitis,
construct a conceptual model that examines two relationship
2006; Neal, Uysal, & Sirgy, 2007, 2009). Milman (1998) points out
quality constructs (customer satisfaction, customer-company
that “an increasing number of tourism and travel promotional
identification) as mediating variables between the lodging service
campaigns suggest that travel, vacation, or any tourism experience
quality perceptions of Chinese tourists and two outcomes
may have a positive impact on a traveler's psychological well-be-
(repurchase intentions, subjective well-being). In the course of the
ing” (p. 166). However, the majority of studies in this area focus on
literature review, we also develop the hypotheses. The results
the relationship of quality of life or the subjective well-being of
follow, and the paper concludes with a discussion of the managerial
residents of tourism destinations, with few studies exploring the
implications of the findings, as well as study limitations and di-
contribution of specific tourism activities to tourists' subjective rections for future research.
well-being. Specially, it remains unclear whether tourism activities
facilitated by hospitality organizations contribute to tourists' sub-
2. Literature review and hypotheses development
jective well-being (Dolnicar et al., 2012).
With Asia predicted to be the world's largest tourist destination 2.1. Service quality
and tourist-generating region by 2020, it is surprising that there
has been a general lack of empirical studies with Asian tourists.
Parasuraman, Zeithaml, and Berry (1988) define service quality
Notably, until China opened its doors to the outside world in 1978,
as the difference between customer expectations of the service to
tourism in the country was virtually non-existent. China has since
be received and perceptions of the actual service received. Based on
become a major tourism market (Lee & Sparks, 2007; Qiu & Lam,
this conceptualization, Parasuraman et al. (1988) developed a ser-
2004). With China's population of over 1.3 billion, tourism au-
vice measurement scale (i.e., SERVQUAL) which includes five
thorities have been focusing more attention on developing China's
quality dimensions (reliability, responsiveness, assurance,
domestic tourism market (Wang & Qu, 2004). The domestic market
empathy, and tangibles). SERVQUAL has been widely accepted by
now makes up more than 90% of the country's tourist traffic and has
scholars, but also criticized for its weaknesses and practical appli-
exhibited continuous growth of around 10% each year in the most
cation (Cronin & Taylor, 1992). In the tourism/hospitality literature,
recent decade (China Travel Guide, 2014). Thus, our theoretical
scholars have developed several domain-specific service quality
model is tested with structural equation modeling (SEM) using a
scales such as LODGSERV (Knutson, Stevens, Wullaert, Patton, & sample of Chinese tourists.
Yokoyama, 1990; Patton, Stevens, & Knutson, 1994), HOLSERV
The current study makes a number of contributions to the
(Mei, Dean, & White, 1999), Lodging Quality Index (Getty & Getty,
tourism/hospitality literature. First, it tests and demonstrates that
2003), and others (e.g., Akbaba, 2006; Albacete-Sa´ez,
perceived service quality plays a significant indirect role in the
FuenteseFuentes, & Llore´ns-Montes, 2007; Ekinci & Riley, 1998;
development of improved repurchase intentions, as well as greater
Tsang & Qu, 2000; Wilkins, Merrilees, & Herington, 2007).
customer subjective well-being in a lodging context. Previous
literature focused on service quality (e.g., Babin, Lee, Kim, & Griffin,
2.2. Relationship quality
2005; Hutchinson, Lai, & Wang, 2009; Kozak & Rimmington, 2000;
Petrick, 2004) has examined the relationship between service
Some authors suggest that relationship quality lacks both a
quality and customer behaviors, but has failed to examine customer
formal definition as well as agreement on what dimensions it
subjective well-being as a consequence.
consists of (e.g., Athanasopoulou, 2009; Huntley, 2006; Woo &
Second, this study incorporates customer-company identifica-
Ennew, 2004), although it is recognized as a higher order
tion as a relationship quality construct and tests its mediating role
construct consisting of several distinct constructs (Dwyer & Oh,
in the effects of service quality on customer repurchase intentions
1987; Kumar, Scheer, & Steenkamp, 1995; Lages, Lages, & Lages,
and subjective well-being. This study, thus, extends our under-
2005). Relationship quality is widely recognized as both a key to
standing of relationship quality by adding customer-company
developing loyal customers (Walsh, Hennig-Thurau, Sassenberg, &
identification as a relational construct. Bhattacharya and Sen
Bornemann, 2010) and an important predictor of customer post-
(2003) suggest that customer-company identification represents a
epurchase behavior (Crosby, Evans, & Cowles, 1990; Kim & Cha.,
deep, committed, and meaningful relationship between company
2002; Morgan & Hunt, 1994). Whereas service quality is an over-
and customer. To the best of our knowledge, previous empirical
all evaluation of a firm's performance, relationship quality is a /
strategic orientation that focuses on improving customer
meaningful customer relationships, yet few empirical studies have relationships.
investigated either the antecedents and/or consequences of
Prior research has investigated a number of distinct relationship
customer-company identification (Keh & Xie, 2009), particularly in
quality constructs such as commitment (Dorsch, Swanson, & Kelley,
a tourism/hospitality service context.
1998; Hennig-Thurau & Klee, 1997; Rauyruen & Miller, 2007;
Service quality perceptions have been tied to a number of pos-
Sevensson, Mysen, & Payan, 2010; Walsh et al., 2010) and trust
itive customer behaviors, yet this relationship is not necessarily
(Bejou, Wray, & Ingram, 1996; Dorsch et al., 1998; Dwyer & Oh,
straightforward. Using a value profit chain perspective would
1987; Kim & Cha, 2002; Moorman, Zaltman, & Deshpande, 1992;
suggest that both customer satisfaction and customer-company
Morgan & Hunt, 1994; Rauyruen & Miller, 2007; Sevensson et al.,
identification would be largely influenced by the perceived value
2010; Walsh et al., 2010). Different authors have also utilized a
that obtaining quality service provides to the customer. In addition,
variety of construct combinations to indicate relationship quality.
a cognitive-emotional-behavioral framework would also support a
For example, Lages et al. (2005) represented relationship quality as
perceived service quality to customer-company identification
the amount of information sharing, communication quality, long-
relationship. Though the impact of service quality on satisfaction
term orientation, and satisfaction with a relationship. Whereas
has been widely examined in previous literature, the potential ef-
Kumar et al. (1995) conceptualized relationship quality as encom-
fect of service quality on customer-company identification has not
passing conflict, trust, commitment, willingness to invest in a
been empirically explored fully. He and Li (2011) indicate that the
relationship, and expectation of continuity. In this study we
more favorable the perception of a service, the greater the level of
examine two distinct dimensions of relationship quality: customer
identification with a service company. Ahearne et al. (2005) posit
satisfaction and customer-company identification.
that “identification is likely to be stronger when customers have
favorable perceptions of the boundary-spanning agent with whom
2.2.1. Customer satisfaction
they interact (e.g., the company's salesperson, customer service,
Oliver (1997) conceptualized customer satisfaction as the cus-
technical representatives, etc.)” (p. 575). Underwood, Klein, and
tomer's fulfillment response: a judgment that a product or service
Burke (2001) indicate that characteristics of the servicescape may
provides a pleasurable level of consumption-related fulfillment. In
assist consumers in developing social identification. Similarly,
the tourism/hospitality literature, prior studies have confirmed that
Ahearne et al. (2005) suggest that consumer perceptions of sales-
customer satisfaction is an important antecedent of key post-
person characteristics can also contribute to the development of
epurchase loyalty intentions and behaviors (Chen & Chen, 2010;
customer-company identification.
Chi & Qu, 2008; Hutchinson et al., 2009; Kozak & Rimmington,
Based on these previous findings, the current study posits the
2000; Su & Hsu, 2013; Su, Hsu, & Swanson, 2014). following hypothesis:
A number of prior studies suggest that service quality is a key
H1b. Perceived service quality has a positive in
determinant of customer satisfaction (e.g., Chi fluence on & Qu, 2008; Cronin, customer-company identi Brady, fication.
& Hult, 2000; Fornell, Johnson, Anderson, Cha, & Bryant,
1996; Hutchinson et al., 2009; Kozak & Rimmington, 2000; Orel
& Kara, 2014). This has been confirmed in a number of tourism
contexts such as cruises (Petrick, 2004), restaurants (Babin et al.,
2.3. Repurchase intentions
2005), and golf tourism (Hutchinson et al., 2009). In view of
these prior results, it is hypothesized that:
Service and relationship quality have been found to act as an-
tecedents to a variety of important customer loyalty behaviors such
H1a. Perceived service quality has a positive influence on overall
as repeat purchase, positive word-of-mouth, and the propensity to customer satisfaction.
pay more (e.g., Cronin et al., 2000; Fornell et al., 1996; Hennig-
Thurau, Gwinner, & Gremler, 2002; Palmatier, Dant, Grewal, &
2.2.2. Customer-company identification
Evans, 2006; Wulf, Odekerken-Schroder, & Iacobucci, 2001; Zei-
Customer-company identification is derived from social identity
thaml, Berry, & Parasuraman, 1996). Understanding how tourism
theory and organization identification. Social identity theory
service evaluations affect economic outcomes is important. Indeed,
(Brewer, 1991; Tajfel & Turner, 1985) suggests that in articulating
service evaluation is confirmed as an important antecedent of
their sense of self, people typically go beyond their personal
behavioral intentions (e.g., Chen & Chen, 2010; Chen & Tsai, 2008;
identity to develop a social identity. Ashforth and Mael (1989)
He & Song, 2009; Hutchinson et al., 2009; Zˇabkar, Brenˇciˇc, &
conceptualize the person-organization relationship as organiza-
Dmitrovi´c, 2010), which are important predictors of economic
tion identification, or a person's perception of oneness with an performance.
organization. Organization identification is the degree to which
In the marketing services literature, many studies have
organizational members perceive themselves and the focal orga-
confirmed that satisfaction is a key antecedent of repurchase in-
nization as sharing the same defining attributes (Dutton, Dukerich,
tentions (e.g., Anderson & Sullivan, 1993; Chang & Chang, 2010;
& Harquail, 1994). This identification helps to satisfy the need for
Cronin & Taylor, 1992; Orel & Kara, 2014; Zeithaml et al., 1996). In
social identity and self-definition.
tourism/hospitality contexts, the relationship between satisfaction
Bhattacharya and Sen (2003) extended the organizational
and revisit intentions has also been widely confirmed in such areas
identification construct to a marketing context via a conceptual
as cruises (Petrick, 2004), golfing (Hutchinson et al., 2009), island
framework of customer-company identification. They suggest that
tourism (Prayag & Ryan, 2012), heritage tourism (Chen & Chen,
customer-company identification is the primary psychological
2010; Su & Hsu, 2013), rural tourism (Loureiro & Kastenholz,
substrate for the kind of deep, committed, and meaningful re-
2011), restaurants (Chang, 2013; Liu & Jang, 2009), and lodging
lationships that marketers are increasingly seeking to build with
(Kim, Kim, & Kim, 2009). Based on the previous findings, the
their customers. Customer-company identification has been
following hypothesis is proposed:
defined as “an active, selective, and volitional act motivated by the
H2a. Overall customer satisfaction has a positive influence on
satisfaction of one or more self-definitional needs” (Bhattacharya & repurchase intentions.
Sen, 2003, p. 77). There would appear to be desirable organizational
benefits to building and maintaining deep, committed, and
Similar to customer satisfaction, customer-company /
identification can also impact customer loyalty (Bhattacharya &
there are still questions to be addressed. Tourists have been found
Sen, 2003; He & Li, 2011; He et al., 2012; Marin, Ruiz, & Rubio,
to generally be in good spirits during the day their trip commences
2009; Martínez & Rodriguez del Bosque, 2013; Perez & Rodriguez
(Nawijn, 2010, 2011), and feel generally happy during their holiday
del Bosque, 2013). According to Social Identity Theory (Tajfel &
compared to everyday life (Nawijn, 2011). However, particular as-
Turner, 1979) and Self-Categorization Theory (Turner, Hogg,
pects of interactive services experienced during the process have
Oakes, Reicher, & Wetherel, 1987), customer-company identifica-
not been investigated although these are likely to affect tourist
tion orientates the customer to become psychologically attached to
subjective well-being (Neal et al., 2007).
and care about a company (Bhattacharya & Sen, 2003), which in
In a health service setting, Dagger and Sweeney (2006) found
turn positively stimulates their loyalty (Marin et al., 2009; Martínez
that service satisfaction positively impacts perceived quality of life.
& Rodriguez del Bosque; 2013; Perez & Rodriguez del Bosque,
Similarly, Neal et al. (1999) found a relationship between the
2013). Findings by Ahearne et al. (2005) point out that “from a
importance of an individual's satisfaction with tourism experiences
social identity standpoint, once a customer identifies with a com-
and their overall quality of life. Neal, Sirgy, and Uysal (2004)
pany, purchasing that company's products becomes an act of self-
expanded on their previous study by examining the role of
expression” (p. 577). These prior findings lead us to propose the
tourism services and found that satisfaction with tourism services following hypothesis:
and experiences, trip reflections, satisfaction with service aspects of H3a. Customer-company identi
tourism phases, and non-leisure life domains all had an influence
fication has a positive influence on repurchase intentions.
on overall life satisfaction. As such, there is support for modeling
customer satisfaction as an antecedent to subjective well-being.
H2b. Overall customer satisfaction has a positive in 2.4. fluence on Subjective well-being subjective well-being.
Subjective well-being is a scientific term for how people eval-
Few studies have explored the relationship between customer-
uate their lives (Diener, Suh, & Oishi, 1997) and refers to the
company identification and subjective well-being. According to
appraisal of one's life as satisfactory (Diener, 1984). The subjective
Bhattacharya and Sen (2003), customer identification with a com-
evaluation of one's life can be based on purely cognitive or purely
pany will result in the customer becoming psychologically attached
affective bases, or it can be based on a combination of the two
to and caring about the firm. Doing so motivates the customer to
(Diener, Emmons, Larsen, & Griffin, 1985). The affective component
interact positively and cooperatively with organizational members,
of subjective well-being refers to how people perceive the balance
helping them to satisfy one or more important self-definition needs
between their pleasant and unpleasant affects, such as joy and
(e.g., self-continuity, self-distinctiveness, and self-enhancement).
sadness. This phenomenon is termed “hedonic balance”
Social interactions constitute one of the ways that tourists can
(Schimmack, Radhakrishnan, Oishi, Dzokoto, & Ahadil, 2002).
contribute to their quality of life (Dolnicar et al., 2012). According to
Others may make judgments about their subjective well-being
attribution theory (Weiner, 1980, 1985, 1986, 1995), when cus-
based primarily on what they believe is important for the fulfill-
tomers' self-definition needs are satisfied, their subjective well-
ment of their goals. Subjective well-being can be conceptualized
being may increase. In line with these discussions, the following
based on experience in a particular domain (e.g., job, consumption, hypothesis is formulated:
family, tourism, health) or on satisfaction with life in general as a
H3b. Customer-company identification has a positive influence
culmination of an individual's current life circumstance (Dagger & on subjective well-being. Sweeney, 2006).
Kotler, Adam, Brown, and Armstrong (2003) note that marketers
should seek to “deliver superior value to customers in a way that
maintains and improves the consumer's and the society's well-
2.5. Mediating hypotheses
being” (p. 20). Using a social marketing perspective, organizational
performance is increasingly being measured by social as well as
Customer satisfaction has previously been found to mediate the
financial outcomes (Clarke, 2001; Tschopp, 2003). The social mar-
effect of service quality on a range of customer loyalty and behav-
keting concept, therefore, defines marketing activity, at least in
ioral intention constructs in a variety of contexts, including su-
part, on the basis of its impact on subjective well-being. Dagger and
permarkets (Orel & Kara, 2014), health services (Dagger & Sweeney,
Sweeney (2006) suggest that in a services context, subjective well-
2006), IT services (Akter, D'Ambra, Ray, & Hani, 2013), and retail
being may be the most relevant outcome of the consumption
(Walsh & Bartikowski, 2013). A recent tourism study that sampled process.
Chinese tourists found that destination satisfaction fully mediated
Researchers of the tourism industry have recently begun to put
the effect of service quality on both revisit intentions and positive
more focus on the social outcomes of tourism development in areas
word-of-mouth referrals (Su et al., 2014). Therefore, this present
such as tourists' quality of life (Andereck & Nyaupane, 2011; Neal
study puts forth the following hypothesis:
et al., 2007), subjective well-being (Filep, 2014), and happiness
H4a. Overall customer satisfaction mediates the in (Nawijn, 2011). fluence of
perceived service quality on repurchase intentions.
Subjective well-being does not conflict with the traditional
financial and growth-oriented objective of tourism and destination
Engaging in leisure activities can affect the emotional, intellec-
development; rather, it strengthens our understanding of the po-
tual, spiritual, and/or physical aspects of an individual's life, which
tential impacts of tourism-based services. Managers, marketers,
in turn may influence the individual's overall sense of well-being
and policy makers can positively impact the lives of tourists
(Dolnicar et al., 2012). More specific to the current study, service
through the subjective well-being concept (Andereck & Nyaupane,
satisfaction has previously been found to play a key mediating role
2011). Tourism-based experiences influence people's quality of life
between service quality and quality of life perceptions in both
(Andereck & Nyaupane, 2011) and improve their subjective well-
health (Dagger & Sweeney, 2006) and IT service contexts (Akter
being (Filep, 2014). Although the relevance of tourist experiences
et al., 2013). Based on these prior findings, we propose that tour-
impacting subjective well-being has been acknowledged (e.g.,
ist evaluations of hospitality-based service encounter quality and of
Andereck & Nyaupane, 2011; Neal et al., 2007; Sirgy et al., 2011),
overall service satisfaction may well affect the quality of life /
perceptions reported by Chinese tourists.
reliability, responsiveness, confidence, and communication) were
assessed with a single adopted question identi
H4b. Overall customer satisfaction mediates the in fied in a pilot study fluence of
(discussion to follow) as most representative of a particular
perceived service quality on subjective well-being. dimension.
A few studies have identified customer-company identification
The measurement of customer satisfaction relied on a three-
as a mediator for a variety of postepurchase consumer behaviors.
item scale adapted from Maxham and Netemeyer (2002). For
Bhattacharya and Sen (2003) suggest that customer-company
customer-company identification, we utilized the well-established
identification may mediate the effect of identity attractiveness on
scale by Mael and Ashforth (1992), which has previously shown
company loyalty, company promotion, customer recruitment, and
good reliability in a hotel industry context (So, King, Sparks, &
resilience to negative information. Hong and Yang (2009) report a
Wang, 2013). Three relevant items were selected from the orig-
critical mediating effect of customer-company identification be-
inal six based on pre-test findings (discussion of pilot study to
tween organizational reputation and customers' positive word-of-
follow). Repurchase intentions were measured via a three-item
mouth referrals. In a business-to-business context, Keh and Xie
scale derived from Arnold and Reynolds (2003). Subjective well-
(2009) confirmed customer-company identification mediates the
being was measured via three items adapted from the Subjective
effect of corporate reputation on purchase intention. Based on
Happiness Scale (Lyubomirsky & Lepper, 1999). All the aforemen-
these previous findings, the present study puts forward the
tioned measures were assessed via five-point, Likert-type scales following hypothesis:
with anchors of Strongly Disagree (1) and Strongly Agree (5).
To establish translation equivalence the questionnaire was H5a. Customer-company identi first
fication mediates the influence of
prepared in English, and the back translation process suggested by
perceived service quality on repurchase intentions.
Mullen (1995) was utilized to identify any content or wording er-
Service quality is an important predictor of customer-company
rors. Specifically, to establish translation equivalence, the ques-
identification (He & Li, 2011; Lam, Ahearne, & Schillewaert, 2012;
tionnaire was first prepared in English and then translated into
Underwood et al., 2001). Identification is based on an individual
Chinese by a native speaker. Back translation into English was
seeing him or herself as psychologically intertwined with the
performed by a second individual, and then the back-translated
characteristics of a group. Strong customer-company identification
English version and the original versions were compared. The
can help customers satiate one or more of their self-definitional
back translation process utilized a third [bilingual] individual to
needs (Bhattacharya & Sen, 2003). Satisfaction of self-definitional
identify any content and wording errors.
needs should result in greater levels of subjective well-being. We
To better ensure the reliability of the measurement scales and
have not been able to identify any published studies that explore
reduce the overall number of scale items, a pilot study was first
the potential mediating role of customer-company identification
conducted with a convenience sample of 50 undergraduate busi-
between service quality and customer subjective well-being. Thus,
ness students from a university located in central China. Each of the
the following hypothesis is investigated:
student participants was pre-screened to ensure that they had
previously been guests at a full-service hotel. The pilot study re-
H5b. Customer-company identification mediates the influence of spondents
perceived service quality on subjective well-being.
first provided suggestions that resulted in some slight
wording changes for some of the scale items. Using SPSS 21.0, a
The conceptual model portraying the network of relationships
reliability analysis was conducted examining Cronbach's alpha
between relationship quality (overall customer satisfaction,
coefficient as well as the item-total statistics (i.e., corrected item-
customer-company identification), its antecedent (perceived ser-
total correlations; Cronbach's alpha if item deleted) to reduce the
vice quality), and consequences (repurchase intentions, subjective
original question pools. The goal was to create a questionnaire that
well-being) is provided in Fig. 1.
was as concise as possible to aid in reducing respondent fatigue and
encouraging participation. The investigated construct scales all
demonstrated acceptable levels of reliability in the pilot test (i.e., 3. Methodology
alpha >.70). Prior to the questionnaire being finalized, four man-
agers of full-service hotels and three faculty members familiar with
3.1. Construct measurement
the topic area also reviewed the questionnaire. Slight wording re-
visions were made based on their suggestions. When no further
Getty and Getty (2003) suggest that an assessment measure of
changes were recommended, the questionnaire was
hotel quality must include dimensions that re finalized for flect the unique na- use.
ture of the lodging industry. As such, they developed the lodging
quality index (LQI). The LQI is based on SERVQUAL (Parasuraman
et al., 1988), but is designed specifically to provide accurate 3.2. Data collection
customer feedback in a lodging context (Getty & Getty, 2003;
Ladhari, 2009). Each of the LQI quality dimensions (i.e., tangibles,
Data was collected from Chinese leisure visitors to Huitang
Fig. 1. Proposed conceptual model. /
Village, China. Located on the banks of the Wujiang River, this area
conducted to assess the reliability, convergent validity, and
of Hunan province is famous for both its scenic beauty and me-
discriminant validity of the latent constructs between service
dicinal hot springs. The administrator for the Bureau of Huitang
quality, customer satisfaction, customer-company identification,
Spring Resort provided permission to conduct the study in ex-
repurchase intentions, and subjective well-being. Hu and Bentler
change for receiving a report of the findings to share with the
(1999) caution that “it is difficult to designate a specific cutoff
participating hotels. The Bureau of Huitang Spring Resort admin-
value for each fit index because it does not work equally well with
istrator contacted three individual hotel managers who all agreed
various conditions” (p. 27). However, to assist with interpretation of
to allow the data collection to take place. Two trained researchers
the findings the following discussion is being provided. Values for
conducted the actual data collection process. The surveying took
the Root Mean Square Residual (RMR) can range from zero to 1.0
place in the lobbies of three different full-service upscale hotels
with well-fitting models obtaining values less than .05 (Byrne,
(i.e., Huatian Hot Spring Hotel, Jintaiyang Hot Spring Vacation
1998; Diamantopoulos & Siguaw, 2000), although values as high
Resort, and Zilongwan Hot Spring International Hotel).
as .08 are deemed acceptable (Hu & Bentler, 1999). Recommenda-
Potential subjects were approached and asked if they would be
tions for Root Mean Square Error of Approximation (RMSEA) cut-off
interested in completing a short questionnaire. If the hotel guest
points have been reduced considerably in recent years. Tradition-
gave a “yes” answer, the survey investigators would ask the
ally, an RMSEA value of less than .05 indicated good fit; in the range
respondent if they were familiar with the hotel and had experi-
of .05e.10 was considered an indication of fair fit, and values above
enced services provided by the hotel. Seating was available for re-
.10 indicated poor fit (MacCallum, Browne, & Sugawara, 1996).
spondents to sit and complete the questionnaires. The investigators
More recently, a cut-off value close to .06 (Hu & Bentler, 1999) or a
stayed available nearby to provide any asked for clarifications while
stringent upper limit of .07 (Steiger, 2007) seems to be the general
respondents completed the questionnaire. Participation in this
consensus. According to Hair, Black, Babin, and Anderson (2010),
study was voluntary and participants' names and contact infor-
c2/df ratios of 3:1 or less are associated with better-fitting models
mation were not requested to protect the respondents' privacy.
when sample size is less than 750. Values of .90 or greater indicate
When retrieving the questionnaires from respondents each ques-
well-fitting models for the Goodness-of-Fit Index (GFI) and the
tionnaire was briefly checked for completeness. The completed
Adjusted Goodness of Fit Index (AGFI) (Hooper, Coughlan, &
questionnaires were collected and provided to the primary
Mullen, 2008). For the Comparative Fit Index (CFI) a cut-off crite-
researcher of the study. Respondents were selected randomly, on
rion of .90 or greater is needed (Hu & Bentler, 1999). For samples of
different days of the week and at different times of the day between
250 or more and observed variables numbering between 12 and 30,
the hours of 9:00 am and 9:00 pm. The researchers distributed a
Hair et al. (2010) suggest a CFI of above .92. For the Normed Fit
total of 600 questionnaires over a two-month period, with 451
Index (NFI), Bentler and Bonnet (1980) suggest that values greater
returned that included complete responses (75.2% response rate).
than .90 indicate a good fit, while Hu and Bentler (1999) indicate
Respondents were all ethnic domestic Chinese and slightly more
that the cut-off criteria be greater than .95. The Relative Fit Index
likely to be female (50.3%). Age categories represented included 16
(RFI) and Incremental Fit Index (IFI) should be equal to or greater
to 24 (41.5%), 25 to 44 (42.1%), and 45 years of age or older (16.4%). A
than .90, while the TuckereLewis Index (TLI) recommendations
wide range of occupations were reported (e.g., business owner,
have had acceptable cutoffs noted as low as .80 (Hooper et al.,
farmer, public servant, sales person, soldier, student, teacher), with 2008).
the level of education ranging from less than high school (17.1%), to
a postgraduate degree (5.1%). The majority of reported individual
4.1.1. Goodness-of-fit measurement model
monthly incomes fell below 4000￥. Complete sample character-
According to the model evaluation criteria suggested in the prior
istics are provided in Table .1.
discussion, the overall fit of the proposed model to data was
acceptable (see Table 2). Specifically, c2/df ¼ 2.031, RMSEA ¼ .048, 4. Empirical analyses
RMR ¼ .025, GFI ¼ .945, AGFI ¼ .922, NFI ¼ .954, RFI ¼ .943,
IFI ¼ .976, TLI ¼ .970, CFI ¼ .976.
The reliability, convergent validity, and discriminant validity of
the investigated constructs were assessed prior to testing the hy-
4.1.2. Reliability test
pothesized relationships in the proposed model.
Findings indicate that all constructs included in the proposed
model achieved acceptable levels of reliability based on Cronbach's 4.1. Measurement model
alpha coefficient exceeding .70 (Fornell & Larcker, 1981): service
quality (.867), customer satisfaction (.863), customer-corporate
To verify the underlying structure of constructs in the proposed
identification (.818), repurchase intentions (.929), and subjective
theoretical model we first conducted a confirmatory factor analysis
well-being (.872). Similarly, composite reliability of the latent
(CFA). Measurement model tests using AMOS 21.0 software were
constructs ranged from .819 to .933 (see Table 2). Table 1 Sample characteristics. n % n % Gender Age in Years Female 224 49.7 16 to 24 187 41.5 Male 227 50.3 25 to 44 190 42.1 45 or Older 74 16.4 Monthly Income Less than 2000￥ 90 20.0 Level of Education 2000 to 2999￥ 96 21.3 Less than High School 77 17.1 3000 to 3999￥ 114 25.3 High School/Technical School 145 32.2 4000 to 4999￥ 69 15.3
Undergraduate/Associates Degree 206 45.7 5000￥or More 82 18.2 Postgraduate Degree 23 5.1 / Table 2
Confirmatory factor analysis results. Latent and observed Variables Mean SD Standard loading t-statistic CR AVE Cronbach's alpha Service Quality
The hotel was visually appealing 3.62 .85 .733 17.211 .867 .567 .867
My reservation was handled efficiently 3.60 .79 .787 19.008
Employees responded promptly to my requests 3.62 .82 .710 16.452
The hotel provided a safe environment 3.48 .84 .761 18.136
Charges on my account were clearly explained 3.56 .86 .772 18.498 Customer Satisfaction
As a whole, I am satisfied with (hotel name) 3.66 .80 .823 20.427 .864 .680 .863
I am satisfied with the overall service that (hotel name) provided to me 3.52 .79 .837 20.943
I am satisfied with my overall experience with (hotel name) 3.53 .85 .814 20.113
Customer-company Identification
I am very interested in what others think about (hotel name) 3.60 .87 .733 16.547 .819 .602 .818
This hotel's successes are my successes 3.56 .88 .842 19.630
When someone praises this hotel, it feels like a personal compliment 3.21 .84 .748 16.966 Repurchase Intentions
I intend to revisit (hotel name) my next trip to this area 3.62 .94 .798 20.268 .933 .823 .929
(Hotel name) would always be my first choice 3.49 .90 .966 27.596
I would like to come back to (hotel name) in the future 3.47 1.00 .949 26.751 Subjective Well-Being
In general, I consider myself a very happy person 3.86 .69 .801 19.510 .875 .701 .872
Compared to most of my peers, I consider myself more happy 3.92 .67 .896 22.882
I am generally very happy and enjoy life 3.89 .71 .811 19.865
Goodness-of-fit: c2/df ¼ 2.031, RMSEA ¼ .048, RMR ¼ .025, GFI ¼ .945, AGFI ¼ .922, NFI ¼ .954, RFI ¼ .943, IFI ¼ .976, TLI ¼ .970, CFI ¼ .976.
4.1.3. Convergent validity test
follows: c2/df ¼ 2.227, RMSEA ¼ .052, RMR ¼ .039, GFI ¼ .940,
According to Anderson and Gerbing (1988), convergent validity
AGFI ¼ .918, NFI ¼ .948, RFI ¼ .937, IFI ¼ .971, TLI ¼ .965, CFI ¼ .971.
is satisfied if the standardized factor loading exceeds .400, is sig-
In comparison with values suggested in the prior discussion, find-
nificant at .001, and average variance extracted (AVE) is greater than
ings demonstrate that the model's fit is satisfactory. Thus, it was
.500. As provided in Table 2, the standardized factor loading of
deemed appropriate to next test the hypothesized paths.
items ranged from .710 to .967, and all were statistically significant
(p < .001). Average variance extracted of the latent constructs
4.2.2. Structural model results
ranged from .567 to .823. The findings suggest that a large portion
The hypothesized positive relationship between service quality
of the variance was explained by the items, and convergent validity
and customer satisfaction (H1a) was supported (l21 ¼ .615, is satisfied.
t ¼ 11.145, p < .001). Hypothesis H1b, which predicted a positive
relationship between service quality and customer-company
4.1.4. Discriminant validity test
identification was also supported (l31 ¼ .462, t ¼ 8.291, p < .001).
According to Chin (1998), discriminant validity is satisfied if the
As predicted by hypotheses H2a and H2b, customer satisfaction
AVE is greater than .500, and the correction coefficient among
significantly impacted both repurchase intentions (b42 ¼ .624,
latent constructs is lower than the squared root of AVE. Construct
t ¼ 11.746, p < .001) and subjective well-being (b52 ¼ .495, t ¼ 8.916,
AVE ranged from .567 to .823, all exceeding .500 (see Table 2). The
p < .05). Customer-company identification was also found to have a
square root of AVE of the latent constructs ranged from .753 to .907,
statistically significant positive influence on repurchase intentions
while the correlation coefficients among latent constructs fell be-
(b43 ¼ .087, t ¼ 1.942, p < .1) and subjective well-being (b53 ¼ .101,
tween .322 and .664 (see Table 3). The findings indicate adequate
t ¼ 1.966, p < .05), providing support for both H3a and H3b. The discriminant validity.
predicted relationships, standardized path loadings, t-values, and
hypotheses test outcomes are provided in Table 4.
4.2. Structural path model
4.3. Power of the model
Once the measurement model was validated, subsequent
structural equation modeling (SEM) analyses were conducted to
According to Cohen (1988) the value of R2 (.01, .09, and .025) can
support the theoretical model and to test the hypotheses.
be used as threshold values to demonstrate small, medium, and
large effects in behavioral models. In the current study, results
4.2.1. Structural model fitting index
suggest that large impacts on the endogenous variables are being
The fitting indices of the structural path model results are as
captured in the model (see Fig. 2), specifically, 37.8%, 21.4%, 42.7% Table 3
Correlation matrix and average variance extracted. Perceived service Overall customer Customer-company Repurchase intentions Subjective well being quality satisfaction identification Service Quality .753 Customer Satisfaction .601 .825
Customer-Company Identification .436 .495 .776 Repurchase Intentions .399 .664 .368 .907 Subjective Well-Being .363 .539 .322 .325 .837
Note: square root of average variance extracted (AVE) is shown on the diagonal of the matrix; inter-construct correlations are shown off the diagonal. / Table 4
Structural model evaluation indices and hypotheses test outcomes. Hypothesis Predicted relationships
Path label Standard Path loadings
T-value Standard error Hypothesis test outcome H1a
Perceived service quality / Overall customer satisfaction l21 .615c 11.145 .055 Supported H1b
Perceived service quality / Customer-company identification l31 .462c 8.291 .062 Supported H2a
Overall customer satisfaction / Repurchase intentions b42 .624c 11.746 .062 Supported H2b
Overall customer satisfaction / Subjective well-being b52 .495c 8.916 .047 Supported H3a
Customer-company identification / Repurchase intentions b43 .087a 1.942 .046 Supported H3b
Customer-company identification / Subjective well-being b53 .101b 1.966 .038 Supported
a Statistically significant (p < .1).
b Statistically significant (p < .05).
c Statistically significant (p < .001).
and 28.3% of the variance for customer satisfaction, customer-
on repurchase intentions and subjective well-being. The model fits,
company identification, repurchase intentions, and subjective
(c2/df ¼ 2.867, RMSEA ¼ .064, RMR ¼ .025, GFI ¼ .965, AGFI ¼ .937,
well-being, respectively. We calculated effect size (G2) by exam-
NFI ¼ .976, RFI ¼ .965, IFI ¼ .984, TLI ¼ .977, CFI ¼ .984), and the
ining the impact of each independent latent variable on each
standardized path coefficients are all statistically significant (see
dependent latent variable using the formula (G2 ¼ (R2
Table 5). Thus, Baron and Kenny's included — first criterion is met. R2excluded)/(1 — R2 ))
provided by Lee, Petter, Fayard, and
Secondly, the constructed structural equation model between
Robinson (2011). The effect size for overall customer satisfaction
perceived service quality and repurchase intentions and subjective
on repurchase intentions is .457. The effect size of overall customer
well-being was found to fit (c2/df ¼ 2.501, RMSEA ¼ .058,
satisfaction on subjective well-being is .213. The effect sizes of
RMR ¼ .043, GFI ¼ .960, AGFI ¼ .937, NFI ¼ .967, RFI ¼ .956,
customer-company identification on repurchase intentions and
IFI ¼ .980, TLI ¼ .973, CFI ¼ .980). The standardized path coefficients
subjective well-being are .016 and .010, respectively.
between perceived service quality on repurchase intentions and
subjective well-being were all statistically significant (see Table 6).
Thus, Baron and Kenny's second criterion is met.
4.3.1. Mediation effects of relationship quality
Next, we constructed a structural equation model including
To test for mediating effects, Baron and Kenny (1986) suggest
perceived service quality, repurchase intentions, and subjective
regressing the (1) mediators on the independent variables, (2)
well-being using overall customer satisfaction as a mediating var-
dependent variables on the independent variables, and (3)
iable (see Table 7). Modeling all direct and indirect paths (see
dependent variables on both the independent variables and me-
Table 8), the results indicate that the overall model fits, (c2/
diators. Based on the Baron and Kenny (1986) method, Hopwood
df ¼ 2.509, RMSEA ¼ .058, RMR ¼ .027, GFI ¼ .945, AGFI ¼ .920,
(2007) pointed out that a structural equation model method has
NFI ¼ .957, RFI ¼ .946, IFI ¼ .974, TLI ¼ .967, CFI ¼ .974). Service
advantages over multiple regression in testing mediating effects. It
quality has a significant effect on customer satisfaction, but not on
is not necessary that mediator models specify observed (measured)
repurchase intentions or subjective well-being. Customer satisfac-
variables, and in many cases there are advantages to specifying
tion is significantly associated with both repurchase intentions and
latent variables. Latent variables are commonly used in applications
subjective well-being. According to the judgment criterion of the
such as structural equation modeling (SEM). One advantage of us-
mediating role suggested by Baron and Kenny (1986), the results
ing latent, as opposed to observed, variables is that the former
indicate that customer satisfaction fully mediates the effect of
tends to estimate the desired effect more reliably because any
service quality on repurchase intentions and subjective well-being.
variables associated with measurement error in a particular
Using the same methods and procedures, we next tested for the
observed variable are unlikely to be shared across other observed
mediating role of customer-company identification. Having previ-
variable(s) and, thus, will not contribute to the score on a shared
ously identified that service quality significantly influences
latent variable (Hopwood, 2007). Thus, unreliability and method
repurchase intentions and subjective well-being, the constructed
effects on models of mediation can be ameliorated through the use
structural equation model between customer-company identifica-
of SEM (Hopwood, 2007). In the current study, all variables are
tion, repurchase intentions, and subjective well-being was found to
latent. So, following Baron and Kenny (1986) method and
fit (c2/df ¼ 1.663, RMSEA ¼ .038, RMR ¼ .052, GFI ¼ .980,
Hopwood's (2007) procedures, we test the mediating roles of
AGFI ¼ .964, NFI ¼ .984, RFI ¼ .977, IFI ¼ .993, TLI ¼ .991, CFI ¼ .993).
customer satisfaction and customer-company identification,
The standardized path coefficients were all statistically significant respectively.
(see Table 9). Baron and Kenny (1986) first criterion is met.
To test the mediating effect of customer satisfaction, we first
Next, the results of modeling all direct and indirect paths of
construct a structural equation model with customer satisfaction
Fig. 2. Structural Model Results. Note: aStatistically significant (p < .1). bStatistically significant (p < .05). cStatistically significant (p < .001). Note: aStatistically significant (p < .1). / Table 5
Standardized path coefficients between overall customer satisfaction and repurchase intentions and subjective well-being. Predicted relationships Standardized Path loadings T-value Standard error
Overall customer satisfaction / Repurchase intentions .658a 12.514 .063
Overall customer satisfaction / Subjective well-being .534a 9.849 .047
Goodness-of-fit: c2/df ¼ 2.867, RMSEA ¼ .064, RMR ¼ .025, GFI ¼ .965, AGFI ¼ .937, NFI ¼ .976, RFI ¼ .965, IFI ¼ .984, TLI ¼ .977, CFI ¼ .984.
a Statistically significant (p < .001). Table 6
Standardized path coefficients between perceived service quality and repurchase intentions and subjective well-being. Predicted relationships Standardized Path loadings T-value Standard error
Perceived service quality / repurchase intentions .408a 7.784 .060
Perceived service quality / subjective well-being .375a 6.884 .045
Goodness-of-fit: c2/df ¼ 2.501, RMSEA ¼ .058, RMR ¼ .043, GFI ¼ .960, AGFI ¼ .937, NFI ¼ .967, RFI ¼ .956, IFI ¼ .980, TLI ¼ .973, CFI ¼ .980.
a Statistically significant (p < .001). Table 7
Standardized path coefficients between perceived service quality on overall customer satisfaction and repurchase intentions and subjective well-being. Predicted relationships Standardized Path loadings T-value Standard error
Perceived service quality / Overall customer satisfaction .599a 10.819 .055
Perceived service quality / Repurchase intentions .005 .090 .065
Perceived service quality / Subjective well-being .068 1.069 .053
Overall customer satisfaction / Repurchase intentions .657a 10.247 .075
Overall customer satisfaction / Subjective well-being .494a 7.316 .057
Goodness-of-fit: c2/df ¼ 2.509, RMSEA ¼ .058, RMR ¼ .027, GFI ¼ .945, AGFI ¼ .920, NFI ¼ .957, RFI ¼ .946, IFI ¼ .974, TLI ¼ .967, CFI ¼ .974.
a Statistically significant (p < .001). Table 8
Direct, indirect, and total effects of service quality on overall customer satisfaction, repurchase intention, and subjective well-being. Predicted relationships Direct effects Indirect effects Total effects
Perceived service quality / Overall customer satisfaction .599a e .599a
Perceived service quality / Repurchase intentions .005 .394a .399a
Perceived service quality / Subjective well-being .068 .296a .364a
Overall customer satisfaction / Repurchase intentions .494a e .494a
Overall customer satisfaction / Subjective well-being .657a e .657a
a Statistically significant (p < .001).
service quality, customer-company identification, repurchase in-
5. Conclusions and discussions
tentions, and subjective well-being are provided (see Tables 10 and
11). The overall model fits (c2/df ¼ 1.719, RMSEA ¼ .040, 5.1. Discussion
RMR ¼ .032, GFI ¼ .962, AGFI ¼ .945, NFI ¼ .967, RFI ¼ .958,
IFI ¼ .986, TLI ¼ .982, CFI ¼ .986), and H5a and H5b are confirmed.
The current study provides and tests an integrated model that
Service quality has a significant effect on customer-company
examines two relationship quality constructs (customer satisfac-
identification, repurchase intentions, and subjective well-being,
tion, customer-company identification) as mediating variables be-
respectively. Customer-company identification also significantly
tween the lodging service quality perceptions of Chinese tourists
impacts repurchase intentions and subjective well-being. Based on
and two outcomes (repurchase intentions, subjective well-being).
suggestions by Baron and Kenny (1986), the results indicate that
Previous research on relationship quality has tended to ignore the
customer-company identification partially mediates the effect of
role of customer-company identification even though it represents
service quality on repurchase intentions and subjective well-being.
deep, committed, and meaningful relationships (Bhattacharya &
We summarize the results regarding the mediating effects of
Sen, 2003) and a close bonding (Keh & Xie, 2009) between a
customer satisfaction and organizational identification in Table 12.
company and its customers. In addition, although subjective well-
being research has received increased attention among tourism
researchers (Dolnicar et al., 2012; Gilbert & Abdullah, 2004; Neal Table 9
Standardized path coefficients between customer-company identification and repurchase intentions, subjective well-being. Predicted relationships Standardized Path loadings T-value Standard error
Customer-company identification / repurchase intentions .381a 7.139 .055
Customer-company identification / subjective well-being .338a 6.094 .041
Goodness-of-fit: c2/df ¼ 1.663, RMSEA ¼ .038, RMR ¼ .052, GFI ¼ .980, AGFI ¼ .964, NFI ¼ .984, RFI ¼ .977, IFI ¼ .993, TLI ¼ .991, CFI ¼ .993.
a Statistically significant (p < .001). / Table 10
Standardized path coefficients between perceived service quality on customer-company identification and repurchase intentions and subjective well-being. Predicted relationships Standardized Path loadings T-value Standard error
Perceived Service quality / Customer-company identification .436a 7.825 .062
Perceived Service quality / Repurchase intentions .297a 5.310 .064
Perceived Service quality / Subjective well-being .279a 4.698 .049
Customer-company identification / Repurchase intentions .244a 4.330 .058
Customer-company identification / Subjective well-being .208a 3.476 .044
Goodness-of-fit: c2/df ¼ 1.719, RMSEA ¼ .040, RMR ¼ .032, GFI ¼ .962, AGFI ¼ .945, NFI ¼ .967, RFI ¼ .958, IFI ¼ .986, TLI ¼ .982, CFI ¼ .986.
a Statistically significant (p < .001). Table 11
Direct, indirect, and total effects of service quality on customer-company identification, repurchase intention, and subjective well-being. Predicted relationships Direct effects Indirect effects Total effects
Perceived Service quality / Customer-company identification .436a e .436a
Perceived Service quality / Repurchase intentions .297a .106a .404a
Perceived Service quality / Subjective well-being .279a .094a .369a
Customer-company identification / Repurchase intentions .244a e .244a
Customer-company identification / Subjective well-being .208a e .208a
a Statistically significant (p < .001). Table 12
Mediation role of relationship quality summary. Hypothesis Mediator Relationship Full mediation Partial mediation Not supported H4a Overall customer satisfaction
Perceived service quality / Repurchase intentions √ H4b Overall customer satisfaction
Perceived service quality / Subjective well-being √ H5a
Customer-company identification
Perceived service quality / Repurchase intentions √ H5b
Customer-company identification
Perceived service quality / Subjective well-being √
et al., 1999, 2007; Sirgy et al., 2011), few studies have explored
effects of service quality and customer-company identification on
antecedents to tourists' subjective well-being.
customer loyalty, but has largely ignored the mediating role that
A number of prior studies have investigated the relationships
customer-company identification could play on customer loyalty
between service quality perceptions, customer satisfaction, and
constructs. This study helps to address these noted gaps in the
repurchase intentions. However, the results of these studies have
literature. We provide empirical validation that customers do,
not been consistent. Some studies indicate that customer satisfac-
indeed, identify with hospitality providers (i.e., lodging) and this
tion has a partial mediating role (e.g., Dagger & Sweeney, 2006;
in-turn provides positive consequences for both the service pro-
Walsh & Bartikowski, 2013). The current study found customer
vider (i.e., repurchase intentions) and the customer (i.e., subjective
satisfaction has a full mediating effect of service quality on
well-being). Specifically, we demonstrate that customer-company
repurchase intentions, which is consistent with the recent findings
identification has a partial mediating effect between perceived
of Su et al. (2014) who sampled tourists in a Chinese heritage
service quality and repurchase intentions, as well as subjective
tourism context. Future research will be needed to help clarify if
well-being. These findings suggest that lodging companies can help
these differences are associated with culture, type of industry, or
satisfy an individuals' self-definitional needs even in the absence of other factor(s).
formal membership. By doing so, this study extends prior research
Although there has been previous exploration of the relation-
on the social identity perspective of customer loyalty through
ship between tourism services, satisfaction with tourism experi-
incorporating subjective well-being as a consequence of customer-
ence, and life satisfaction (Neal et al., 1999, 2004, 2007; Sirgy et al., company identification.
2011), one contribution of the current study is the identification of
the full mediating role that satisfaction plays between service
quality and the subjective well-being of Chinese tourists. This
5.2. Managerial implications
finding is not consistent with Dagger and Sweeney (2006) who
found service satisfaction to partially mediate the effect of service
Not surprisingly a key take-a-way from this study is that hos-
quality on quality of life in a health service setting. One explanation
pitality firms need to provide a high level of service quality.
of the differing results may be that tourists are likely to be primarily
Perceived high levels of service quality help to cultivate a satis-
focused on obtaining satisfactory experiences when on holiday,
factory relationship with customers and foster greater customer-
whereas in a health service context, customers will assign a greater
company identification, in turn promoting customer repurchase
importance to the quality of service received.
behavior and improved subjective well-being. In particular, hotel
This study introduces the customer-company identi
managers should make an effort to develop a distinctive, service fication
construct into a tourism/hospitality context. Recently, Martínez and
quality based corporate identity that resonates with their core
Rodriguez del Bosque (2013) pointed out that “despite the recog-
customers. To achieve such an identity, it will be important for
nized importance of customer-company identi
lodging managers to first determine the relative importance of fication, its effects
on the development of hotel customer loyalty remain relatively
various quality dimensions and track these, as well as overall unexplored”
quality, over time to identify trends. The measurement of perceived
(p. 96). Extant literature has focused on the direct
performance on both overall quality and individual quality /
dimensions will be useful to help hotel managers target areas for
commitment, communication quality, conflict) into our model.
improvement at individual properties, as well as providing a means
Future researchers may also want to consider the relationship
to identify performance differences between properties (if man-
ordering between perceived service quality and any investigated
aging multiple lodging locations). In addition, it is important to
proposed relationship quality constructs. For example, although the
assess competitor performance to identify possible quality differ-
perceived service quality to customer-company identification
ences. Relative performance differences on individual quality di-
ordering appears to have substantiation in the literature, this
mensions can then be used as the basis for competitive
relationship is not necessarily straightforward and does not pre- differentiation.
clude the possibility that there may be a reverse relationship.
Given the positive consequences of customer-company identi-
The students participating in the pilot study were pre-screened
fication, tourism/hospitality managers and marketers should
to ensure experience with lodging services. The investigated
consider the level of resources required to incorporate into their
construct scales did demonstrate acceptable levels of reliability in
strategy decisions the elements that drive customer-company
the pilot test and, again, in the actual study with our population of
identification. Service companies may be more likely to benefit
interest, hotel guests. However, to more properly screen scale items
from identification than firms that focus on selling goods since the
for appropriateness, the pretest should have used respondents
inseparability of consumerecompany interactions helps to facili-
more similar to those from the population to be studied. Finally, the
tate customer engagement and, thus, identification (Bhattacharya
data used in this research are cross-sectional in nature, which raises
& Sen, 2003). To build identification, hospitality-based organiza-
concerns about the causal relationships between constructs in the
tions must devise strategies for meaningful customer-company
tested model. Stronger evidence of causality via longitudinal and/or
interactions that embed customers in the organization and make
experimental studies is needed.
them feel like insiders. Rather than focusing only on acquiring new
customers, hospitality managers must emphasize the retention and Acknowledgment
enhancement of customer relationships as a strategic focus.
The process of forging stronger bonds with customers can start
This research was supported by the National Science Foundation
with tracking information about purchases and using that infor-
for Young Scholars of China (No. 71203240), the State Key Program
mation to offer financial incentives. This does not simply mean that
of National Natural Science of China (No. 71431006); the Founda-
the hospitality organization charges lower prices. Rather, this
tion for Innovative Research Groups of the National Natural Science
retention strategy financially rewards customers for more pur-
Foundation of China (No. 71221061), the State Key Program of
chases or relationship longevity via loyalty programs (e.g., frequent
National Natural Science of China (No. 71431006) and Tourism
guest discounts or perks). The next challenge is to combine finan-
Young Expert Training Program (TYEPT201436).
cial incentives with interpersonal bonds between the customer and
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Geographical Research, Economic Management Journal,
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Economic Geography; and four papers in English scholarly
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journals, such as Journal of Hospitality & Tourism Research,
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and Journal of Travel & Tourism Marketing.
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Scott R. Swanson (Ph.D., University of Kentucky) is a
Professor of Marketing at the University of WisconsineEau
Xiaohong Chen is professor of management in the Busi-
Claire (swansosr@uwec.edu). His research interests
ness School of Central South University. Her current
include Sports and Hospitality/Tourism Marketing, Service
research interests include decision support systems,
Recovery Issues, and Pedagogy. Dr. Swanson has published
resource-saving and environment-friendly marketing
more than 50 papers in journals such as the Journal of the
management, enterprise financing, and entrepreneurship.
Academy of Marketing Science, Journal of Marketing
Dr. Chen has presided over thirty national, ministerial
Theory and Practice, International Journal of Contempo-
and provincial projects, including five projects supported
rary Hospitality Management, and Journal of Hospitality &
by National Natural Science Foundation of China. She has
Tourism Research, among others. He has presented his in-
published twenty books and over three hundred research
sights to audiences in Asia, Europe, South American and
papers in authoritative journals of high quality both at
North America and conducted 50 + business consulting home and abroad.
projects over the past 10 years.