Journal of Quality Assurance in Hospitality & Tourism
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Perceived Experience, Perceived Value and
Customer Satisfaction as Antecedents to Loyalty
among Hotel Guests
Daly Paulose & Ayesha Shakeel
To cite this article: Daly Paulose & Ayesha Shakeel (2021): Perceived Experience, Perceived
Value and Customer Satisfaction as Antecedents to Loyalty among Hotel Guests, Journal of Quality
Assurance in Hospitality & Tourism, DOI: 10.1080/1528008X.2021.1884930
To link to this article: https://doi.org/10.1080/1528008X.2021.1884930
Published online: 15 Feb 2021.
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JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
https://doi.org/10.1080/1528008X.2021.1884930
ARTICLE
Perceived Experience, Perceived Value and Customer
Satisfaction as Antecedents to Loyalty among Hotel Guests
Daly Paulose and Ayesha Shakeel
Department of Management Studies, St. Teresa’s College, Ernakulam, Kerala, India
ABSTRACT
KEYWORDS
Despite the hospitality industry reeling under the impact of
COVID-19, few studies provide practitioner-oriented perspec­
tives capturing dimensions of guest loyalty within emerging
markets. The researchers examine the influence of perception
of value and experience on guest loyalty within the context of
the Indian hotel industry. A random questionnaire survey of 170
occupants across three renowned hotels during the first week of
COVID-19 induced lockdown in India and subsequent analysis
using structural equation modeling confirm that both guest
loyalty and satisfaction continue to be positively influenced by
perception of value and the service experience. Both guest
satisfaction and loyalty are strongest among guests who per­
ceive high service value. Guest loyalty is also indirectly influ­
enced by value perception and service experience through the
mediation of customer satisfaction. The relationship between
perceived experience and guest satisfaction is found to be
stronger when perceived service value is higher. The hospitality
industry, a vector of pandemic occurrence, can use this oppor­
tunity to reset business models. While micro-segmentation is
called for in positioning offerings to target groups, efforts to
reduce customer sacrifice by simplification of pricing and trans­
action procedures should be implemented across the spectrum
in adjusting to the new normal.
Experience; customer loyalty;
customer satisfaction;
perceived value; lodging;
leisure
Introduction
Leisure travel has become a norm today, with individuals considering it
integral to well-being. The total contribution of travel and tourism to the
global economy in 2019 was US 9.5 USD trillion. Of this, the global leisure
travel spend in 2019 alone was US 4.715 USD billion (Lock, 2020). The
revenue in the hotels segment alone amounted to US 383,081 USD million
in 2019–20, and was expected to show a CAGR of 4.1% in 2020 (Statista
Market Forecast, 2019). The growth story in India – the seventh largest
tourism economy in the world and touted to be the fourth largest by 2027 –
had been phenomenal too with 8.5% of the country’s GDP and 8.7% of
employment opportunities being generated by the sector. The lodging
CONTACT Daly Paulose
dalypoulose@teresas.ac.in
Avenue Road, Ernakulam, Kerala 682011, India.
© 2021 Taylor & Francis Group, LLC
Dept of Management Studies, St Teresa’s College, Park
2
D. PAULOSE AND A. SHAKEEL
segment of India’s tourism sector (also known as the hotel industry) alone was
worth US$22 billion while clocking a YoY growth rate of 7% until the events of
2020 (Ministry of tourism, 2020).
With the unexpected onslaught of the COVID-19 pandemic in 2020, sky­
rocketing international tourism numbers have fallen like a stone with fore­
casted trends shifting dramatically from the predicted 4% annual growth to
a 20–30% decline for 2020. With residual fears running high from the
one million deaths registered worldwide from the pandemic and international
air travel rapidly slowing, the hospitality sector has become the horrific face of
the COVID-19 pandemic. Epidemics have a proven detrimental impact on
travel behavior and subsequently hotel occupancy due to mounting health and
safety concerns (Hung et al., 2018; Jiang & Wen, 2020). With occupancy
declining rapidly in lodging services, tourism and tourism subsectors (F&B,
lodging and transportation services) are likely to report the greatest pressure
with mounting losses to the tune of 150% quarter to quarter (Ministry of
tourism, 2020). Researchers need to focus on supplementing the limited
literature at hand with empirical studies to assist the hotel industry with
practical data-driven insights and workarounds on the path of resurgence.
Though the concept of loyalty has received considerable attention in the
literature, the jury is still out on its antecedents with perceived quality,
customer trust, satisfaction, engagement and receiving weightage in different
contexts. Of late, antecedents like perceived customer experience, customer
delight and customer co-creation of value are gaining momentum (Rather &
Hollebeek, 2019). The pandemic has pressurized the hospitality sector to
create bankable Value for Money (VFM) business models resting on higher
trust and relationship bonds with customers (Rather et al., 2018). Relationship
building by focusing on brand credibility and trust guarantee an easier ride on
the road to resurrection. Loyalty also leads to brand advocacy – a powerful and
free marketing tool with loyal customers acting as reliable advocates on social
media, casually bringing friends, family and other potential customers on
board (Kandampully et al., 2015; See-To & Ho, 2014). By buying more,
spending more and recommending more, consumer evangelists singlehand­
edly salvage businesses in times of economic recession (Gossling et al., 2020).
Since loyalty is developed over time by consistently meeting and sometimes
exceeding customer expectations (Teich, 1997), service providers can increase
their customer base 25–100% by focusing on relationship management alone
(Griffin, 2010).
Guest evaluation of the consumption experience is enhanced by a sound
experiential marketing strategy. A successful experiential marketing strategy
will enhance satisfaction and customer loyalty leading to high repurchase
intention (Kuo, 2013). Once a customer has engaged with the brand, he or
she is left with a clear and memorable comprehension of complex brand values
along with mental heuristics of price–value relationships. This experience, if
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
3
curated appropriately, connects with the intrinsic and extrinsic motivations of
the customer and blooms into an authentic relationship (Smilansky, 2009).
Most studies on customer loyalty view customer satisfaction as an inevitable
predictor that positively affects repurchase intention, word of mouth and share
of wallet (Hollebeek & Rather, 2019). Even though the relationship seems
almost intuitive, it has been found to vary significantly in strength under
different conditions (Chang et al., 2009). Add to this the chaos of the pan­
demic, where even satisfied consumers are likely to switch to easily accessible
alternatives and the need to relook at this existing relationship between
customer satisfaction and loyalty is paramount.
The present study examines the relationship between guest satisfaction and
loyalty factoring in the predictive influence of perceived value and perceived
experience, in the context of the Indian hotel industry. It also examines how
these interrelationships differ for occasional and frequent guests. It is worth
noting that no empirical study in India to date has investigated all these
constructs in a single framework. The novelty dimension of the study rests
in being one of the earlier empirical studies to bring pandemic-induced
perspectives into hotel guest responses. Considering the huge paucity of
contextual empirical data needed to guide response mechanisms of the hotel
industry reeling under the impact of the pandemic, the present research paper
is an answer to Gossling et al. (2020) call for reviewing antecedents to
customer loyalty in the hospitality sector.
The study intends to (i) propose and validate a research model to study
interrelationships with the loyalty construct using the SEM approach, (ii)
examine the mediating effects of customer satisfaction on the relationships
between perceived value/perceived experience and customer loyalty, (iii) study
the moderating effect of perceived value on the relationship between experi­
ence and satisfaction.
Literature review and hypothesis development
The self-congruity theory defines value congruity as a mental comparison
made by customers between the firm’s values and their own set of values
(Johar & Sirgy, 1991). A study by Rather et al. (2018) and Rather and Camilleri
(2020) in the hotel context reveal that value congruity and social identity
positively effect customer-brand identification, and through that, brand
engagement and ultimately brand loyalty. Therefore, hoteliers need to identify
the values that are considered to be important in connecting to their target
customers. Research suggests that consumers in emerging markets like India
are becoming increasingly materialistic, but all the while remain price sensitive
and value conscious at the core (Kesari & Atulkar, 2016; Sharma, 2011). The
imminent economic slowdown is likely to further exemplify the role of
customer perceived value as being critical to service strategy (Jiang & Wen,
4
D. PAULOSE AND A. SHAKEEL
2020). Experiential aspects like service customization (Ball et al., 2006), per­
sonal interaction management (Jones & Farquhar, 2003) and feelings of
pleasure and enjoyment at the service encounter (Wong, 2004) are also
integral to customer loyalty. It follows that the interplay of perceived experi­
ence and value together satisfies consumers and build brand patronage and
customer loyalty (Chang & Wang, 2011; El-Adly, 2019).
Perceived experience
Experiential marketing signifies a two-way communication between the brand
and the target audience in real time, featuring a live brand experience at its
essence. Since live experiences materialize through five touch-points in deliv­
ery – sense, feel, think, act, and relate marketing – the choice of marketing
channels is critical in amplifying this experience. The term ‘perceived experi­
ence’ relates to customer perception about the experiential dimensions of the
service on offer and is a prerequisite to customer engagement (Konuk, 2019;
Rather, 2020; Smilansky, 2009). Customer Engagement is recognized as
a strategic imperative for developing customer–firm relationships, especially
in the marketing and hospitality sector. Customers who are engaged and
involved with the hospitality brand tend to be more satisfied, committed and
loyal (Konuk, 2019; Rather & Sharma, 2019). Since customer absorption and
attention levels are critical predictors of engagement, service marketers must
ensure that positive news and publicity linked to the brand is packaged well
(Rather & Sharma, 2019). Technology tools like big data analytics can then be
used to design customized service packages by modeling interrelationships
between marketing efforts, consumer experience, and customer loyalty
(Rather, 2020).
Hollebeek and Rather (2019) & Wilkins et al. (2007) claim that consumers
are more likely to remember desirable experiences, and these experiences are
likely to affect their perception of service quality. While service quality and
innovativeness are known triggers of positive customer engagement outcomes
that create a desirable effect on perceived brand experience (Rather &
Hollebeek, 2019; U.I. Islam et al., 2019), the combined impact of social identity
theory and social exchange factors on brand loyalty cannot be undermined in
a hospitality context (Rather & Camilleri, 2020). These service experiences in
turn are a function of the physical service environment, customer interaction
with staff as well as other customers and hence the distinct role of each
individual dimension needs to be understood (Ali et al., 2016). Encouraging
customers to share such experiences upfront on social media platforms
impacts brand resonance (Rather & Hollebeek, 2020) and such online com­
munities foster organic conversations that personify and grow the brand
(Hollebeek et al., 2017). Thus, managing consumers’ experiential environment
is critical to sustaining competitive advantage in the tourism industry. The
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
5
bottom line is that a well-designed and executed service experience has
a significant effect on guest satisfaction and purchase intention (Frías
Jamilena & Rodríguez Molina, 2013).
Perceived value
According to Pham and Huang (2015), perceived value is the consumer’s
overall assessment of the net worth of a product/service based on perceptions
of what is received and what is given. In other words, perceived value is the
result of a relative evaluation of benefits and costs associated with an offering.
For business continuity, customer perceptions of this ratio of benefit to cost
must be comparable to the firm’s benefit-to-cost ratio. While perceived value is
usually measured in terms of functions of price, quality and sacrifice (Chang
et al., 2009), in the lodging segment latent dimensions like self-gratification,
sensory perception, prestige value and hedonism assume more prominence
than just price and quality (El-Adly, 2019). Independent studies by Rather
et al. (2018) and Wilkins et al. (2007) extoll firms focused on relationship
marketing to shift focus from profitability metrics alone and focus on value
creation for customers. Being a collectivist society where social identities
matter, Indians espouse the Social Identity Theory (SIT) perceiving value in
brand identification (Rather & Hollebeek, 2019). Studies done in the e-shop­
ping domain also point toward an strong linkage between customer responses
and perception of value (Hsu, 2006; J. U. Islam et al., 2020)
Customer satisfaction
Customer satisfaction is a customer’s fulfillment from a product or service
experience, derived by comparing expected and perceived performances
(Hanan et al., 1989). In contrast to the cognitive nature of perceived value,
Lin (2015) claims that the customers’ satisfaction level is the emotional and
psychological evaluation of individual consumer experience. Researchers have
identified several outcomes of customer satisfaction as being brand credibility,
relationship continuity, brand advocacy and greater share of purchase wallet
(Rather & Hollebeek, 2019; Shams et al., 2020).
Customer loyalty
According to Oliver (1999, p. 33), customer loyalty is “a commitment to rebuy or re-patronize a preferred product/service consistently in the future”.
Loyalty can incorporate behavioral or attitudinal dimensions with repurchase
intention, being behavioral and brand advocacy, being attitudinal (R.A.
Rather, 2018). Customers will be loyal and maintain relationships if they
think that the value provided by the supplier is superior to alternative offerings
6
D. PAULOSE AND A. SHAKEEL
(Bharadwaj & Matsuno, 2006). Reichheld and Sasser (1990) establish that
when a service company retains 5% more of its customers, their profits rise
by 25% to 125%. The concept of loyalty is of specific importance in the service
sector on account of greater risk associated with service intangibility. In the
hospitality sector, loyalty is largely shaped by affective rather than cognitive
attributes, which is probably why repeat-tourists are found to be more loyal,
when compared to first-time tourists (Leckie et al., 2016; Rather, 2020). This
implies that loyalty is born out of activation and personalization efforts
provided to repeat customers, with brand trust at the epicenter (R.A Rather
et al., 2019a). In addition to customer patronage, investing in relationship
marketing also makes clients less price sensitive and perceptions of quality are
also incidentally improved. While service innovativeness and competence
trigger behavioral loyalty, proactive conflict resolution, customer trust build­
ing measures and consistent delivery of service promise amplify attitudinal
customer loyalty (Narteh et al., 2013).
Relationship between perceived experience and customer satisfaction
It is deemed that creating personal experiences will provide future compe­
titive edge for service companies. According to Schmitt (1999) and Prahalad
and Ramaswamy (2000), the motive of marketing, in terms of customer
satisfaction, is not only to solve customer problems or to give them the
required benefits but also to provide a holistic and valuable experience.
According to Tseng et al. (2009), guests today demand more than just
a product or service to fulfill their needs. They crave for an experience that
goes beyond their augmented expectations. Hanefors and Mossberg (2003)
found that those customers with memorable experiences showed intense
feelings of joy, inquisitiveness, excitement and involvement – all of which
converged into feelings of satisfaction (Rather & Camilleri, 2019). As affec­
tive components predominantly influence customer response in the hospi­
tality sector, the relevance of ‘engagement through experience’ cannot be
underplayed (Ali et al., 2016). While the role of ‘servicescape’ and physical
evidence in boosting employee performance and customer satisfaction is well
known (Sahoo & Ghosh, 2016), there is sufficient research in the hotel
business to prove that heightened customer participation in service recovery
efforts offers lasting customer engagement opportunities that are capable of
significantly impacting the service experience of existing customers in the
system and perceptions of potential customers outside it (Rather, 2019; Raza
et al., 2020).
Thus, it is imperative for hotel marketers to understand the significance of
various experiential dimensions and their impact on customer satisfaction
(Tseng et al., 2009; El-Adly, 2019). It can be hypothesized from the above
relationships that
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
7
H1a: Perceived experience with service is positively associated with customer
satisfaction.
Relationship between perceived experience and customer loyalty
As customers stay at hotels for recreation and leisure, it is a given that
experience is an integral part of what guests claim they want and what
recreation resource managers try to furnish (U.I. Islam et al., 2019).
According to Gronholdt et al. (2000), customer loyalty consists of four mea­
sures – price tolerance, repurchase intention, inclination toward recommend­
ing a brand to friends and family, and readiness to go for cross-purchase. By
managing the service experience effectively, the relationship between consu­
mer and brand maybe strengthened (Hollebeek, 2011; Leckie et al., 2016;
Rather & Camilleri, 2019). Research conducted in the tourism setting in
India discloses that brand experience, along with value congruence and desti­
nation credibility significantly affects brand recall, subsequently impacting
tourists’ attachment, advocacy and loyalty toward the destination (Rather
et al., 2019b). Involving customers in the brand experience is found to have
a direct and positive impact on brand loyalty and repurchase intention (Leckie
et al., 2016). This is reflected in the repeat vacation market, where a good prior
experience with the brand offsets risk and uncertainty for travelers, since the
perceived risk associated with choosing a known service provider is less
(Konuk, 2019; Lehto et al., 2004). In a pandemic inflicted world, brand
experiences are kept alive through online customer engagement initiatives
that rely on user-generated content creation, influencer marketing and con­
necting on social media. The customer brand connect established through
channels for online engagement is showing traction in the present scenario
(Goh & Okumus, 2020). Previous research in the e-commerce domain also
validates the important role of experience dimensions like website environ­
ment in driving website traffic and repeat conversions. In a study in the hotel
context, Rather (2019) and Rather and Sharma (2019) propose that there is
a non-linear relationship between engagement and loyalty, suggesting that the
impact of brand engagement on loyalty is likely to backfire after a tipping point
and thereafter highly engaged customers tend to display lower levels of
attitudinal loyalty, caused by fatigue and burnout. Considering that service
failures are inevitable in the highly intangible hospitality sector, such out­
comes could be indicative of complacency in service response arising from
customer familiarity. A renewed focus on customer co-created service recov­
ery measures may do the trick in keeping customer spirits high. Such cocreation strategies in service recovery process are known to boost positive
customer emotions, perceived justice, satisfaction, and reuse intentions among
8
D. PAULOSE AND A. SHAKEEL
customers (Shams et al., 2020). Hence, it is proposed to revisit the following
hypothesis.
H1b: Perceived Experience of service is positively associated with customer
loyalty levels.
Relationship between perceived value and customer satisfaction
Kotler (2003) stated that consumers are spoiled for choice when it comes to
competitive service offerings. Difficult decision-making is made possible by
weighing the value offered by the service provider against the cost that the
consumer must pay. As per the economic theory of utility, rational consumers
will try to derive maximum utility from minimal resources (time, energy,
budget and cognitive capabilities) – making perceived customer value an
integral precursor to purchase intention. Given that value is a function of
quality vis-à-vis cost of service, it automatically tilts the customer satisfaction
function favorably. Hospitality brands are known to facilitate creation and
expression of social identity with customers quick to forge brand associations
that match their self-concepts. With satisfaction in the hospitality sector being
primarily driven by emotional nuances, strong identification with service
offerings are likely to lead to positive customer outcomes, like higher brand
loyalty and greater price tolerance (Ali et al., 2016; R.A. Rather, 2018). It
follows that customers who identify well with a hotel brand perceive greater
value and tend to be more satisfied by virtue of psychological brand attach­
ment (Rather & Hollebeek, 2019).
Application of relationship marketing theory is useful in linking higher per­
ceived value of a service to higher levels of customer satisfaction and long-term
financial gains for firms (Ulaga, 2001; Cronin et al., 2000; Rather & Camilleri,
2020; Eggert & Ulaga, 2002). It follows that if the measurement of customer
satisfaction does not involve an in-depth understanding of customer value and
related emotions that influence evaluation of the service, it may not provide
managers with adequate information to respond well. Hence, the researchers
propose to reassess this relationship through the following hypothesis.
H2a: Customer perception of value is positively associated with customer
satisfaction.
Relationship between perceived value and customer loyalty
In comparison to products, loyalty is difficult to achieve in the service sector
due to the characteristics of services such as intangibility, lack of
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
9
standardization, inseparability and extensive customer involvement in service
delivery (Bloemer et al., 1998; Mittal & Lassar, 1998). Multiple researchers
claim that customer perceived value is a significant predictor of customer
loyalty, that is, greater the consumer’s perception of value, the more likely they
are to convey a willingness to buy the product again (Ryu et al., 2012;
McDougall & Levesque, 2000; Ishaq et al., 2014). In a study on the tourism
industry, El-Adly (2019) also established a positive effect of perceived value on
customer retention and loyalty. So, if the guests have a positive perceived value
from a hotel’s service, they are more likely to be loyal and revisit. Rather et al.
(2018) introduced the role of value congruity in positively influencing loyalty
as well as brand engagement levels in hotel guests. perceived value emerges the
strongest predictor of customer patronage. Loyalty behavior such as the con­
tinuance of the relationship increase in the scale or scope of the relationship
and recommendation to others (through word of mouth) are a result of the
customers’ confidence that the value provided by one supplier is more sig­
nificant than that obtainable from other suppliers (Tseng et al., 2009). Studies
based on Indian samples additionally highlight the importance of brand
authenticity in determining value perceptions. Perceived value for money
derived from authentic brand relationships negates the need to search for
alternative service providers and customer loyalty results (Rather et al., 2019b).
These insights have led to the proposal of the following hypothesis
H2b: Customers’ perception of value is positively associated with customer
loyalty.
Relationship between customer satisfaction and customer loyalty
According to Goh and Okumus (2020), increased customer satisfaction paves
the way for greater purchase frequency, creates larger share of wallet purchases
and generates positive word of mouth. A satisfied customer is more likely to
spend more money, stay loyal (Chen, 2012) and recommend the business
positively to others (Babin et al., 2005; El-Adly, 2019; Lee et al., 2007). Rather
et al. (2019b), in a study conducted in India, confirmed that customer satisfac­
tion has a significant positive impact on loyalty and behavioral intention, and
as the cost of attracting a new customer is 6–15 times more expensive than that
of holding on to an existing one, hospitality managers need to find ways to
increase customer satisfaction, as well as loyalty and prevent customers from
switching. The issue here is that hoteliers tend to inflate customer expectations
to retain and gain business. In consonance with the expectation disconfirma­
tion theory (EDT), the resultant inability of hoteliers to meet the high stan­
dards consistently negatively impact loyalty levels (R.A Rather et al., 2019a).
Multiple studies show that superior value creation from the complete service
10
D. PAULOSE AND A. SHAKEEL
experience including post purchase follow-up forms the instrumental link
between customer satisfaction and loyalty (Cronin et al., 2000; Gallarza &
Saura, 2006; Kesari & Atulkar, 2016). It is worth mentioning that millennials
primarily evaluate brands on trust and view corporate social responsibility and
corporate citizenship measures as well when forming perceptions and attach­
ments to brands (U.I. Islam et al., 2019). Several studies centered around the
hotel industry claim that guests who are satisfied tend to be loyal and willing to
revisit and add more in customer life-time value (CLV) terms (McDougal &
Levesque, ; Kandampully & Suhartanto, 2003; Tseng et al., 2009). The satisfied
guests in these studies are less likely to browse pre-travel information sources,
more likely to contribute in terms of average length of stay, spend extensively
within hotel premises and engage in destination activities. They are also will­
ing to revisit, as well as spread positive word of mouth about the hotel.
Therefore, the following hypothesis is proposed to validate these claims.
H3: Customer satisfaction is positively associated with customer loyalty.
Mediating role of customer satisfaction in the experience–loyalty relationship
It is a well-known fact that satisfied customers are willing to repurchase/endorse
brands based on prior experience and perceptions (Kuo, 2013). Research done
within the hospitality industry identified that several experiential elements like
overall landscape and décor, food arrangement, employee demeanor and com­
petence, tailored experiences, surprise elements, etc., create lasting impact on
customers. This positive interaction experience culminates in instant customer
delight leading to long-term customer patronage (Gupta et al., 2007; Sahoo &
Ghosh, 2016). For customer loyalty to evolve from experiential service cocreation and resultant customer brand identification, customer satisfaction is
a must (Leckie et al., 2016; R.A. Rather, 2018). However, few studies examine
differential attitudes toward service experience due to shopping motivation
being hedonic or utilitarian (Kesari & Atulkar, 2016). As little is known about
this mediatory role in emerging markets, the following hypothesis is postulated.
H4a: Customer satisfaction mediates the relationship between perceived experi­
ence and customer loyalty
Mediating role of customer satisfaction in the value–loyalty relationship
Just as perceived value involves evaluation of net utility from a service, custo­
mer satisfaction also refers to the overall positive or negative feeling about
a service. While the former reflects a cognition function, the latter has more to
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
11
do with feelings. Hence, satisfaction is bound to be significantly influenced by
perceived value (Yang & Peterson, 2004; Choi, 2019; Tarun & Chopra, 2007).
The positive influence of perceived value on customer satisfaction and
repurchase intentions has been well documented in the services marketing
literature (Heung & Ngai, 2008; Tseng et al., 2009) as has the role of relational
constructs like trust and commitment on guest loyalty within the hotel sector
(R.A. Rather, 2018). It is also argued that in an experiential economy, merely
offering services at good value may not be sufficient to impress customers or
guarantee customer loyalty (El-Adly, 2019; Lin, 2015). Due to contradictory
views, the following hypothesis is tested
H4b: Customer satisfaction mediates the relationship between perceived value
and customer loyalty
Interaction effect of perceived value in the experience–satisfaction relationship
Studies have indicated that the relationship between customer satisfaction and
customer loyalty becomes strongest when customers perceive that their cur­
rent business vendor offers greater overall value than competitors (Chang
et al., 2009). Several studies have also established that it is a consumer’s
experience during the service encounter that basically translates into satisfac­
tion with the service provider (Kuo, 2013). It is also possible that the influence
of perceived value on customer satisfaction is significantly affected by prior
experience (Frías Jamilena & Rodríguez Molina, 2013). Considering that no
study so far has combined both effects to examine the role of perceived value
in enhancing the relationship between perceived experience and customer
satisfaction, the following hypotheses are proposed
H5a: Perceived value amplifies the relationship between perceived experience
and customer satisfaction
H5b: Perceived value amplifies the relationship between perceived experience
and customer loyalty
Control variable in the model
Research has shown that repeat purchase intention (an indicator of customer
loyalty) is strongly linked to consumer involvement and satisfaction with
recent service received (Lehto et al., 2004). In the context of leisure travel,
consumer involvement would be a function of the time/effort invested in
itinerary planning and the attitude toward travel itself (referred to as travel
affinity in the study). If an individual exhibits favorable attitude toward travel,
his/her travel affinity is deemed to be high. In the hospitality industry, where
leisure travel and lodging operations complement and feed off each other, the
impact of travel affinity on intention to make leisure trips has a spillover effect
12
D. PAULOSE AND A. SHAKEEL
on hotel stay too (Choi, 2019; Kandampully et al., 2015). It follows that this
presence/absence of travel affinity in an individual is bound to impact percep­
tion toward all service providers in the hospitality domain (Josiam et al., 2000).
As travel affinity is entirely intrinsic to an individual’s personality and belief
system and has no bearing on the service provider whatsoever, it is logical to
control for its extraneous influence on guest loyalty.
The hypothesized relationships derived from the existing literature have
been depicted in the conceptual model (modified from Tseng et al., 2009)
presented in Figure 1. This model is also loosely based on Bagozzi’s (1992) selfregulation processes and the Stimulus-Organism-Response theory (Rather
et al., 2019b) in which appraisal processes lead to emotional responses,
which then result in coping strategies. Here perceived value and experience
constitute the evaluation/appraisal phase, customer satisfaction depicts emo­
tional reaction and customer loyalty stands for the response/behavior
component.
It has been consistently established by (Jiang & Wen, 2020; Leckie et al.,
2016; Rather, 2020) that repeat tourist groups are the largest revenue source to
accommodation providers in terms of average length of stay, spending on food
and recreation and use of hotel amenities. This maybe attributable to the
affective aligned and risk mitigating decision-making style observed among
customers in this sector. This could mean that frequency of hotel stay has
a long-standing impact on the various constructs in the model as well as on
future intention to revisit.
Appraisal Process
Coping Response
Emotional Reaction
TRAVEL AFFINITY
Direct Effect
Control Variable
Figure 1. Conceptual Model for Antecedents of Customer Loyalty (Modified from Tseng et al.
(2009))
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
13
The following hypotheses are tested considering their relevance to the body
of knowledge.
H6: Intention to revisit is dependent on guests perceived value of service, satisfaction
levels and loyalty to recent service provider.
H7: The relationship between guest loyalty and perceived value, perceived
experience and satisfaction differs based on frequency of hotel stay.
Methodology
Sample
The original instrument proposed by Tseng et al. (2009) was subjected to
several rounds of content validation in consultation with three eminent
academicians and three senior service personnel from the hotel industry.
Based on unanimous expert advocacy for brief scales, a few repetitive items
were removed with the intent of minimizing item redundancy (Chaudhary &
Dey, 2016). Items under the same subscale that seemed repetitive were com­
bined to capture unique dimensions. Finally, the different dimensions were
measured using four different scales with a total of 24 items of which 9 items
measured perceived experience, 8 items measured perceived value, 4 items
denoted customer satisfaction and 3 items measured customer loyalty. The
questionnaire, which was whetted by industry and academic experts, was
pretested among 50 participants lodged at a luxury hotel in Kerala during
the first week of March 2020. Except for minor cosmetic changes and removal
of four items which showed loadings <0.3, no other alterations were made to
the new instrument. Data for the main study were incidentally collected
during the last week of March 2020 (during the first phase of lockdown in
India to combat COVID-19) from among occupants stranded at three differ­
ent properties of a luxury hotel chain spread across Kerala. The respondents
were chosen by systematic random sampling of guest list from the hotel’s
reservation desk and the responses were collected online with the immense
support of hotel management. Selected respondents were briefed about the
academic purpose of the survey and that participation was totally voluntary.
As the questionnaire contained generic and contextual statements, respon­
dents were instructed to answer the ‘contextual questions’ based on their most
recent leisure trip experience. The questionnaires were handed over to the 240
randomly chosen guests after seeking their informed consent through inter­
vention of the hotel management. Yet several of these participants chose not to
respond to the survey and even after the 14 days allotted, 45 questionnaires
remained unanswered. After further eliminating 25 questionnaires that were
returned but incomplete, the final sample consisted of 170 responses
14
D. PAULOSE AND A. SHAKEEL
comprising 70 (41.2%) men and 100 (58.8%) women. Ages of respondents
ranged from 15 to 72 years, with a mean age of 33 years (SD = 13.110).
Measures
The questionnaire used for the pilot study was an improvised scale developed
by Tseng et al. (2009) that combined four subscales developed from Czepiel
et al. (1974), Pullman & Gross’s (2004), Mathwick et al. (2001), Schmitt’s
(1999)tools and scales. After expert validation, the pruned down inventory
consisted of 24 questions in all that were subjected to slight alterations to
render it suitable for the hotel setting. All these responses were taken on
a 5-point Likert scale, with 1 for “Strongly Disagree” and 5 for “Strongly
Agree”. An additional section focused on classification data (such as age,
gender, monthly income, frequency of vacationing).
Results and analysis
Respondent description
The relevant demographic and behavioral characteristics for the respondents
of the main study are outlined in Table 1
Item reduction and scale validation
The study uses a modified version of the conceptual model proposed by Tseng
et al. (2009) for exploring the concept of customer loyalty. The data from the
pilot study were subjected to principal component method for the purpose of
item reduction. The items whose highest loadings were greater than 0.4 were
retained in the pool while those which displayed poor loadings were removed
from subsequent stages of exploratory factor analysis. Reliability coefficient α
was examined and scale items that increased adjusted item-to-total correla­
tions when removed were deleted. At the end of the item generation and item
screening procedures, the researchers used EFA to (i) determine the number
of underlying factors/constructs, (ii) identify the items that load onto specific
factors, and (iii) eliminate any further items if required.
For this phase, the revised questionnaire with 20 items (four items were
removed namely ‘ Going on a kitchen tour reflects a person’s love for experi­
ences’, ‘Experiences during hotel stays make me think of my lifestyle’, ‘ Leisure
stay experiences help me escape everyday pressures’, Attractive exterior and
interior designs in hotels prompt me to think) was administered among a new
sample of 170 respondents and the results of EFA were interpreted. The
Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.945
which met the fundamental requirements for factor analysis. The Bartlett’s
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
15
Table 1. Classification Details of Respondents
Demographic Characteristics
Gender
Monthly Income(INR)
Frequency of Visit
Travel Affinity
Age Distribution
Number of Respondents
Percentage
Male
70
41.2
Female
100
58.8
Less than 20,000
58
34.1
20,000–50,000
22
12.9
50,000–80,000
29
17.1
80,000–1,00,000
20
11.8
More than 1,00,000
41
24.1
Monthly
36
21.2
Every few months
83
48.8
Once a year
51
30
Yes
101
59.4
No
69
40.6
Mean = 33.24; Std Deviation = 13.110; Minimum = 15; Maximum = 72
test of Sphericity showed that non-zero correlations exist at the significance
level of 0.001 (The χ2 test statistic was 2628.379 significant at p = .001).
The psychometric properties of the measures were assessed using explora­
tory factor analysis with varimax rotation, coefficient alpha, and adjusted itemto-total correlations. The use of maximum likelihood method of extraction
along with Varimax rotation provided a clearer separation of the factors (Hair
et al., 1998). All factors with computed eigen values greater than one were
retained in the solution. The final step of EFA involved determining which
items loaded onto the prescribed factors. As a result of factor analysis, 20 items
with factor loading and communalities above 0.5 (Table 2) were retained in the
solution and the clear separation of four factors was obtained. The resultant
factor structure is shown in Table 2. These four factors with eigen values
greater than 1.0 accounted for 66.45% of the total variance in the correlation
matrix. The Cronbach’s alpha coefficient was used to assess the internal
consistency among the set of the items loading on each factor. Each of the
factors had satisfactory Cronbach’s alpha values ranging from 0.927 to 0.847
thereby confirming the internal consistency of the scales.
Common method bias testing
To verify the existence of Common Method Bias in the data, Harman’s singlefactor test was adopted. Since the variance explained by the first factor
(44.975%) did not meet the cut off of 50%, the existence of CMB on the results
can be ruled out.
Confirmatory factor analysis
Structural Equation Modeling is applied for testing the measurement and
relationship models of the study where confirmatory factor analysis recon­
firms how well the observed variables represent their respective constructs.
16
D. PAULOSE AND A. SHAKEEL
Table 2. Exploratory Factor Analysis Results of Four-Factor Customer Loyalty Model
Factor-Wise Listing of Dimensions
Communalities
Perceived Experience
I like experiencing innovative themes in hotels
0.658
I like self-service because I can experience the
0.526
hotel better
I enjoy listening to music/live shows in hotel
0.522
lobbies
I would like to experience a live kitchen
0.613
I pay attention to interior décor in hotels
0.524
Perceived Value
I would explore a hotel’s facilities only if price0.812
value suits me
I feel a hotel must be evaluated based on worth of
0.842
money spend
In comparison to competition, a hotel’s pricing
0.682
must be fair
A hotel must offer good value for money’s worth
0.658
above all
Customer Satisfaction
I like the internal ambience of the hotel
0.791
I experienced high quality service here
0.550
Stay at this hotel was comfortable
0.754
The hotel met my expectations
0.517
The hotel landscape made me want to take
0.567
pictures for memory
I was satisfied with the food served at the hotel
0.648
I was satisfied with the hotel amenities
0.776
I was satisfied with the view from the restaurant
0.568
and the rooms
Customer Loyalty
I am willing to revisit this hotel again
0.854
I would recommend this hotel to others
0.815
I am willing to join this hotel’s loyalty program
0.637
Factor
Loading
Eigen
Value
1.160
%
Variance Reliability
4.912
0.847
0.893
0.676
0.588
0.581
0.532
1.178
5.993
0.903
10.917
2.693
0.927
0.810
2.855
0.902
0.935
0.730
0.622
0.539
1.068
0.719
0.719
0.660
0.660
0.652
0.630
0.618
0.874
0.722
0.527
KMO = 0.945; Bartlett’s test statistic (χ2 = 2628.379 significant at p < .001); number of items = 20; variance
explained = 66.5%.
Assessment of multivariate normality
According to Byrne (2010), items with skewness values >3 and kurtosis values
>7 indicate substantial departure from normality. Table 3(a) reveals that the
skewness and kurtosis values of the items are within acceptable ranges indicat­
ing multivariate normality.
Subsequently, the measurement model generated in Figure 2 was found to
exhibit adequate fit (χ2 = 272.502, df = 159, χ2/df = 1.714, CFI = 0.956,
GFI = 0.885, TLI = 0.947, RMSEA = 0.065, PCLOSE = 0.055,
SRMR = 0.0465). Further, all factor loadings in the measurement model
were greater than 0.5.
The internal validity of the measurement model was examined. Convergent
validity was supported in the model as all loadings were found to be significant
(at 1% level). Second, the construct reliability for each construct exceeded the
recommended level of 0.70 and the average variance extracted (AVE) values
for each construct exceeded 0.50 (Hair et al., 2010). Discriminant validity of
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
Table 3. Table Showing the Skewness and Kurtosis
Values of Items
Item
Revisit willingness
Recommend
Loyalty program
Explore more
Worth money
Pricing reasonable
Value for money
Experience innovation
Self service
Music
Live kitchen
Interior decor
Internal ambience
Service quality
Stay comfortable
Expectation met
Exterior landscape
Food quality
Hotel amenities
Restaurant view
Skew
−.955
-.871
-.495
-.663
-.382
-.706
-.838
-.292
-.106
-.152
-.646
-.123
-.343
-.573
-.884
-.864
-.289
-.635
-.733
-.704
Kurtosis
.194
.095
.189
-.353
-.461
.596
.445
-.565
-.097
-.176
-.444
-.709
-.640
.281
.935
.329
-.801
.018
.873
.129
Figure 2. Measurement Model with Standarized Regression Weights and Factor Correlations
17
18
D. PAULOSE AND A. SHAKEEL
the model constructs was also established from Table 3(b) where ASV values
were less than AVE values and AVE values along the diagonals were greater
than the squared correlations with other constructs shown below it.
The results from measurement model testing presented in Table 3 are
indicative of convergent validity of constructs.
Testing the structural model and hypothesis
Structural equation modeling using AMOS 24 was undertaken using the
maximum likelihood estimation method in order to obtain the causal model.
The fit indices obtained pointed toward adequate model fit model fit.
(χ2 = 4.597, df = 3, p > .05, χ2/df = 1.532, CFI = 0.996, GFI = 0.989,
AGFI = .947, TLI = 0.987, RMSEA = .056, PCLOSE = 0.364, SRMR = 0.045)
Since the fit measures were adequate, the path coefficients of the structural
model were examined. From Table 5, it may be observed that both perceived
experience and perceived value appear to significantly impact both customer
satisfaction and subsequent loyalty.
The path diagram output based on the results of Path analysis is shown in
Figure 3. The final conceptual model highlighting the significant paths and
their factor loadings is presented in Figure 3. The R2 values indicate that 59%
of the variance in Customer Satisfaction is predicted by the constructs
Perceived experience and Perceived value. The variability in Customer
Loyalty is predicted upto 69% by the predictor constructs. Based on Lehto
et al. (2004) and Josiam et al. (2000), the effect of extraneous variable, travel
affinity on customer loyalty was controlled as it could significantly impact
customer loyalty toward service providers of travel-related experiences.
Testing for mediation effects
The indirect effect of the mediator variable Customer Satisfaction on the
relationship between the independent constructs (Perceived Value and
Perceived Experience) and Customer Loyalty was examined and the results
are provided in Table 6, Table 5.
For the path between Perceived Value and Customer Loyalty, there
appeared to be a drop in strength when the mediator was added while indirect
effects were still significant. Hence, it can be said that Customer satisfaction
Table 3(b). Results for Composite Reliability and Construct Validity Tests
Reliability Check Convergent Validity Check
CR
AVE
Satisfaction
0.924
0.648
Experience
0.847
0.526
Value
0.909
0.715
Loyalty
0.905
0.758
Discriminant Validity Check
MSV Satisfaction Experience Value Loyalty
0.647
0.805
0.493
0.696
0.725
0.722
0.804
0.651
0.846
0.722
0.802
0.702
0.845 0.870
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
19
Table 5. Standardized Estimates and Test of Convergent Validity of Constructs
Research Construct
Customer Satisfaction
Items
Std Factor Loading
CR
Conclusion
Internal ambience
Service quality
Comfortable stay
Expectations met
Exterior landscape
Food quality
Hotel Amenities
Room with a view
0.769
0.719
0.870
0.890
0.710
0.805
0.898
0.742
10.689***
9.579***
10.377***
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Significant
Innovation
Self-service
Music and scent
Live kitchen
Interior esthetics
0.712
0.709
0.721
0.751
0.732
8.403***
Explore more
Worth money
Fair pricing
Value for money
Willingness to revisit
Recommend
Loyalty program
8.631***
9.690***
10.670***
8.982***
Perceived Experience
8.503***
8.824***
8.620***
Significant
Significant
Significant
Significant
Significant
0.851
0.931
0.814
0.779
16.519***
13.166***
12.267***
Significant
Significant
Significant
Significant
0.894
0.909
0.812
17.638***
14.040***
Significant
Significant
Significant
Perceived Value
Customer Loyalty
**p < 0.05; ***p < 0.001.
partially mediates the effect of perceived value on customer loyalty (Barron
and Kenny, 1986). Partial mediation was re-confirmed by performing the
significance test using bootstrapping in AMOS. The indirect effect of perceived
value on customer loyalty was significant p = .00, 95% CI (0.093,0.383). For the
path between Perceived Experience and Customer Loyalty, there was a drop in
strength when the mediator was added, though still significant. It was inferred
that the path between perceived experience and customer loyalty was partially
mediated by customer satisfaction. The indirect effect of perceived experience
on customer loyalty was also significant p = .000, 95% CI (0.036,0.190).
Additionally, the significance of both indirect effects was reconfirmed using
Sobel test (For Perceived Value → Customer Loyalty, Sobel’s statistic = 4.513,
p < .000; For Perceived Experience →Customer Loyalty, Sobel’s statis­
tic = 3.270, p < .000)
Table 6. Regression Weights Table of Structural Model
Dependent
Satisfaction
Satisfaction
Loyalty
Loyalty
Loyalty
Loyalty
Independent Variable
Perceived experience
Perceived value
Customer satisfaction
Perceived value
Perceived experience
Travel affinity
**p < 0.05; ***p < 0.001.
Estimate
.471
1.122
.165
.338
.134
−.124
Std Estimate
0.256
0.593
0.369
0.400
0.164
−0.022
S.E.
.110
.113
.030
.055
.045
.241
C.R.
4.271
9.896
5.512
6.097
2.979
−0.517
p Value
***
***
***
***
.003
.605
20
D. PAULOSE AND A. SHAKEEL
Figure 3. (a) Path Diagram Showing standardized Regression Weights, (b) conceptual Model with
Significance of Hypothesized Relationships
Testing for interaction effects on customer satisfaction
The main effects and the interaction effects of the independent constructs
(Perceived Experience and Perceived Value) on Customer satisfaction were
examined from Table 6. It was found that both main effects (βperceived value
= 0.618, p = .000; βperceived experience = 0.271, p = .000) and interaction effects
(βinteraction = 0.135, p = .007) were significant for customer satisfaction with the
main effect of perceived value on customer satisfaction being stronger. But
when it came to the effects of Perceived experience and Perceived value on
Customer Loyalty, only the main effects were found to be significant. Main
effect of Perceived experience on customer loyalty (βperceived experience = 0.164,
p = .003) was found to be lesser than main effect of Perceived value on
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
21
customer loyalty (βperceived value = 0.400, p = .000) while the interaction effect of
the two on customer loyalty was found to be insignificant (βinteraction = −0.061,
p = .174).
Finally, it is inferred from Figure 4 that Perceived Value strengthens the
positive relationship between Perceived Experience and Customer
Satisfaction. When perceived value is low, there is a negative relationship
between perception of the experience and satisfaction. When perceived value
is high, there is a positive relationship between Experience and customer
satisfaction. Hence, we can say that the interaction between the two
Independent variables (Perceived value and Perceived Experience) has
a significant effect on the Dependent Variable (Customer satisfaction).
Testing for interaction effects on customer loyalty
It was found that customer loyalty varied significantly based on both perceived
value and experience, when the groups were analyzed using ANOVA (See
Table 8, Table 7, Table 8). As expected, customers with high perceived
Customer Satisfaction
y = 2.312x + 0.702
Moderator
Low Perceived Value
High Perceived Value
y = -0.32x + 2.31
Low Experience
High Experience
Figure 4. Interaction Effects of Perceived Value and Experience on Customer Satisfaction
Table 7. Testing for Mediation Effects
Relationship
Perceived Value →Customer Loyalty (through
Customer Satisfaction)
Perceived Experience →Customer Loyalty
(through Customer Satisfaction)
Direct Effect (without Direct Effect (with
Mediator)
Mediator)
0.618 (p = .000)
0.400 (p = .000)
0.260 (p = .000)
0.164(p = .003)
Indirect Effect
Significant
(p = .000)
Significant
(p = .000)
22
D. PAULOSE AND A. SHAKEEL
Table 8. Main Effects and Interaction Effects of Constructs
DV
SATISFACTION
SATISFACTION
SATISFACTION
LOYALTY
LOYALTY
LOYALTY
LOYALTY
Independent Variable
PERCEIVED_EXPERIENCE
PERCEIVED_VALUE
EXPERIENCE x VALUE
TRAVELER_SATISFACTION
PERCEIVED_EXPERIENCE
PERCEIVED_VALUE
EXPERIENCE x VALUE
Estimate
.498
1.170
.658
.165
.134
.338
−.133
Std Estimate
0.271
0.618
0.135
0.369
0.164
0.400
−0.061
S.E.
.108
.112
.243
.030
.045
.055
.098
C.R.
4.598
10.407
2.709
5.512
2.979
6.097
−1.361
P value
***
***
.007
***
.003
***
.174
Table 8. Interaction Effects of Perceived Value and Experience on Customer Loyalty
Customer
loyalty
Sample size N
F value
p Value
Low Perceived Value
Low Perceived
High Perceived
Experience
Experience
9.76
11.67
70
High Perceived Value
Low Perceived
High Perceived
Experience
Experience
12.47
14.21
45
18.740
.000
17
38
10.674
.002
experience and high perceived value came out top on all loyalty parameters.
An interesting observation was that customer loyalty was consistently high for
customers with high perceived value, irrespective of the experience scores.
Customers with low perceived value and high experience scores (mean = 11.67)
appeared less loyal than those with high perceived value and low perceived
experience scores (mean = 12.47).
Group classification based on intention to revisit
The researchers desired to understand customer intention to revisit in the near
future, considering the imminent social and economic risks from the pan­
demic globally. ‘Intention to revisit in near future’ refers to the likelihood to
spend time, money and effort on leisure travel with lodging services in the near
future. The prediction was made using guest preference for service
Experiences, Perception of Value and Satisfaction with recent holidaying
experience and Loyalty to service provider as independent variables in
a simple canonical discriminant analysis to generate classification functions.
The discriminant function generated was found to be statistically significant.
The discriminant function explained 24% of the variance (eigen value = 0.063,
canonical correlation coefficient = 0.244, Wilks Lambda = 0.904, chi
square = 10.215, df = 4, p < .037). The assumption of equality of covariances
of IVs in all groups was met as Box’s M value was not significant at 5% level.
Hence, the predictor variables explained about 24% of the variation in inten­
tion to revisit soon.
Table 9 depicts significance levels for differences between group means for
each independent variable. It was observed that while differences were sig­
nificant for all predictors, the biggest contributors to the discriminant function
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
23
Table 9. Tests of Difference Between Group Means for Independent Variables
Customer loyalty
Perceived value
Customer satisfaction
Perceived experience
Wilks’ Lambda
.960
.943
.957
.981
F
6.931
10.233
7.556
3.247
df1
1
1
1
1
df2
168
168
168
168
Sig.
.009
.002
.007
.073
Table 10. Correlation Coefficients Between Independent Variables and
Discriminant Function
Discriminant Function
Independent Variable
Perceived value
Customer satisfaction
Customer loyalty
Perceived experience
High Correlations
0.980
0.842
0.806
Moderate Correlations
0.552
by way of lower Wilks Lambda values were Perception of Value, Satisfaction
and Loyalty.
An examination of the discriminant function loadings in Table 10
revealed that the function corresponded most closely to perception of
value, satisfaction with recent holiday experience and loyalty to service
providers. These variables showed greater discriminating power between
those respondents who were likely to expend on lodging services in the
near future and those who were not. From the correlation coefficients, it
was concluded that value conscious travelers who had a satisfactory holi­
day experience recently and were loyal to specific service providers were
distinctly more likely to avail lodging facilities on a leisure trip in the near
future. However, respondents with a preference for experiential holidays
did not exhibit as distinct a propensity to go on a leisure trip that involves
lodging in the imminent future.
From Table 11, it was seen that the discriminant function correctly
classified 67% of the sample overall. This is in accordance with Hair et al.
(1998) who postulated that classification accuracy must be at least onefourth times greater than the cutoff value (50%) to create meaningful
group profiles. Additionally, the model succeeded in classifying 72% of
the respondents who showed high intention to revisit and 50% of the
respondents with lower inclination.
Table 11. Category Prediction Using Classification Table for ‘Intention to Revisit’
Predicted Values
Intention to Revisit in Near Future
Observed Values
Intention to revisit in near future
Low
High
Overall percentage of accuracy in classification
Low
18
38
High
18
96
Percentage Correctly Classified
50%
72%
69%
24
D. PAULOSE AND A. SHAKEEL
Table 12. Determinants of Guest Loyalty Based on Frequency of Visit (occasional/frequent)
Occasional Visitor
Perceived experience
Perceived value
Customer satisfaction
Std Beta
0.123
0.418
0.392
Frequent Visitor
T
Sig
2.097
0.038*
5.496
0.000**
5.273
0.000**
F = 97.125
Significance = 0.000
R2 = 0.691
Std Beta
0.409
0.354
0.145
T
Sig
3.212
0.030*
2.507
0.017*
0.747
0.460
F = 20.892
Significance = 0.000
R2 = 0.662
Notes: Dependent Variable – Guest Loyalty.
**Significant at p < 0.01 level; * Significant at p < 0.05 level.
Table 13. Summary of findings.
H#
Hypothesis
H1a Perceived experience of service positively influences
customer satisfaction levels.
H1b Perceived Experience of service positively influences
customer loyalty levels.
H2a Customer perception of value positively influences
customer satisfaction.
H2b Customers’ perception of value positively influences
customer loyalty.
H3 Customer satisfaction positively influences customer
loyalty.
H4a Customer satisfaction mediates the relationship
between perceived experience and customer
loyalty
Sign
(+)
Estimate
β = 0.26
Decision
Supported
(+)
β = 0.17
Supported
(+)
β = 0.59
Supported
(+)
β = 0.40
Supported
(+)
β = 0.37
Supported
(+)
H4b Customer satisfaction mediates the relationship
between perceived value and customer loyalty
(+)
H5a Perceived value amplifies the relationship between
perceived experience and customer satisfaction
(+)
Direct effect without
mediator = 0.260 (p = .000)
Direct effect with
mediator = 0.164 (p = .003)
Direct effect without
mediator = 0.618 (p = .000)
Direct effect with
mediator = 0.400 (p = .000)
(βinteraction = 0.135, p = .007)
H5b Perceived value amplifies the relationship between
perceived experience and customer loyalty
(+)
H6
(+)
H7
Intention to revisit is dependent on guests’ perceived
value of service, satisfaction levels and loyalty to
recent service provider.
The relationship between guest loyalty and perceived
value, perceived experience and satisfaction varies
based on frequency of visit.
(+)
Partial
mediation
supported
Partial
mediation
supported
Interaction
effect
Supported
Interaction
supported
F(low perceived value) = 18.740,
p = .000
F(high perceived value) = 10.674,
p = .002
r(perceived value) = 0.980,
Discriminating
r(satisfaction) = 0.842,
power
r(loyalty) = 0.806
supported
F(occasional) = 97.125; p = .000
Supported
F(frequent) = 20.892; p = .000
Comparison of dependence relationships across groups
It is evident from the multiple regression results of Table 12 that value
perception has a stronger influence than experiential attributes in determining
customer loyalty levels for occasional visitors. Frequent visitors exhibit higher
loyalty toward service providers who focus on experience rather than value
attributes.
The findings of the study are summarized in Table 13.
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
25
Discussion
Theoretical implications
The findings of the study confirm all the interrelationships between the
exogenous and endogenous constructs of the model. Perceived value from
the service seems to have the most significant influence on both response
variables – Guest satisfaction and Brand Loyalty (β = 0.59 and β = 0.40,
respectively). These beta coefficients hint at the indispensability of these
constructs in future studies on loyalty. Around 69% of the variation in Guest
Loyalty is explained by the four predictors together while 59% of the variation
in Guest satisfaction is due to the explanatory power of Perceived value and
Perceived experience put together. The rational variable ‘perceived value’
appears to be more important that ‘perceived experience’ in the scheme of
things. This agrees with findings from existent literature by Tarun and Chopra
(2007) and Sharma (2011) that exemplify the price-value consciousness of
Indian consumers.
Customer satisfaction partially mediates the relationship between perceived
value and customer loyalty. It also mediates the relationship between per­
ceived experience and loyalty. In an era characterized by plethora of consump­
tion choice, habitual and incentivized loyalty are becoming things of the past
while committed loyalty (where degree of customer allegiance to brands is
high) is gaining traction. Studies by Babin et al. (2005) and Lee et al. (2007)
prove that being a satisfied customer is a prerequisite for transcending from
habitual (behavioral) to committed (attitudinal) loyalty. For this reason, while
the direct relationship between the predictor and response variable continues
to exist, it drops in strength in comparison to the indirect effect supporting
partial mediation effect.
As observed by Chang et al. (2009) and Kuo (2013), perceived value
plays a moderating role in the relationship between perception of
service and traveler satisfaction. The value perceived by a customer
in a service amplifies the relationship between perception of service
experience and satisfaction levels. When perceived value from
a service is high, the relationship between perception of the service
experience and satisfaction derived from it shows a positive relation­
ship and vice versa. This is to say that when consumers do not
perceive good value in a service, even a positive service experience
need not result in improvement in customer satisfaction. Similarly, in
the presence of a good price-value equation, a good service experi­
ence can positively impact customer satisfaction levels. These results
are in agreement with previous findings by Cronin et al. (2000) and
Ulaga (2001). However, it remains that the main effect of perceived
service experience on customer satisfaction is more significant than
the interaction effect. This could be because 68% of the study’s
26
D. PAULOSE AND A. SHAKEEL
respondents are millennials who have a known craving for experi­
ences (Twenge, 2010).
The researchers could not find enough support for the interaction effect of
perceived service experience and perceived value on the response variable,
customer loyalty. A scenario may exist where a satisfied customer is not
successfully converted into a loyal one – hinting at a gap in existing customer
retention strategies of service providers.
Respondents who showed higher intention to revisit in the immi­
nent future exhibited higher perceived need for value, had higher
satisfaction levels from recent holidaying experience and were loyal
to specific hospitality service providers, as was inferred from the
results of Discriminant Analysis. This group largely comprised
women, aged 35 years and below (whose average monthly income
was around INR. 50000) and nurtured a strong affinity for travel. It
follows that service marketers need to focus on the repeat market of
young, value conscious women because their loyalties can be won
over easily. The overall accuracy of the classification at 67% was
indicative of acceptable predictive validity for the model. Contrary
to expectations, respondents with a preference for experiential holi­
days did not exhibit a similar intention to revisit in the imminent
future. This may be indicative of the expensive nature of experiential
offerings in the Indian hospitality scenario or reflect a temporary
postponement in discretionary spending in the wake of the pandemic.
Perceived values prominently influenced customer loyalty levels for
occasional visitors. Frequent visitors, on the other hand, seemed to imbibe
their loyalty from perceived experiential dimensions at the hotel more
than perceived value. This is perhaps due to the hedonic nature of
hospitality products where first-time guests are influenced by functional
attributes while repeat customers give importance to affective attributes
(Morais & Lin, 2010). Hence, when dealing with the repeat market, service
providers can do well to cater toward emotional, social and epistemic
service needs.
Practical implications
For the average Indian, the act of evaluating what is fair or deserved
against perceived cost of an offering is a prerequisite to customer patron­
age (Sirdeshmukh et al., 2002). The takeaway for practitioners is that the
more important perceived value is, the more influence price changes may
have on guest patronage. In keeping perceived value as the foremost
focus, the challenge to hoteliers lies in resource planning to maximize
customer value without compromising on quality. When it comes to
promotions too, providers need to adopt the rational route of persuasion
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
27
as it directly relates to the price-value conscious personality of the Indian
vacationer. The lower (albeit significant) influence of perceived experience
as a determinant of guest satisfaction and guest loyalty maybe attributable
to the nascent levels in ‘experiential curation’ of service providers in
emerging markets like India. In collectivist societies where people prefer
making leisure trips in groups, service providers have largely laid empha­
sis on ‘value creation’ as opposed to ‘experience creation’. But a postpandemic world characterized by social distancing norms is likely to
create new markets for solo travel, exclusivity and responsible travel.
Service providers may consider brand repositioning through curation of
fresh experiences in mindful tourism – experiences that integrate the
tourist into the local society and its ways. Public good forms of tourism
including social tourism, educational tourism, citizen science, community
exchange tourism and slow tourism could also find takers (Lapointe,
2020). Hoteliers can also do well to use green hotel attributes as selling
points.
To meet the changing traveler demands in a pandemic era, service providers
must develop strong service recovery plans in all identified areas of customer
dissent. After all, a sound service recovery strategy is known to reinforce the
relationship between service experience and satisfaction and discourage cus­
tomer switching (Kuo, 2013; Shams et al., 2020). As demand for responsible
travel to secluded spaces is going to gain traction, Indian hoteliers who have
allowed authentic, trustworthy relationships to evolve from the consumption
experience through personal interaction and customization will find takers.
These bonds of trust need to be capitalized to further promote zero-carbon
norms in a more resilient tourism business model that involves co-created
customer value. The sectors’ growth must cease to be measured in volume
terms and adopt “mass” to “class” tourism development practices.
With distancing norms in place and service providers catering to fewer
clients they will require more space, charge more rent resulting in costlier
stay – bringing the experience factor back in vogue again. The managerial
implication for business owners is to maintain a good price-value equation by
offering acceptable (read: novel and inclusive) quality/experience at attractive
prices with the objective of raising customer perceived value. Offers could
involve increasing functional and psychological benefits (image value) and
decreasing customer sacrifice by simplifying prices and transaction processes.
The dining experience, which is an integral aspect to guest satisfaction may
have to assume innovative avatars: from fine dining to drive-throughs, dining
in silos or room service in the current scenario. The concept of staycations and
bleisure (business + leisure) travel are also going to gain traction among homeridden working professionals, who would jump at the opportunity of working
in a changed ambience under an extended work from hotel (WFH) scheme.
With the paradigm shift towards healthy lifestyles, curated experiences in
28
D. PAULOSE AND A. SHAKEEL
health tourism are also likely to win over the patronage of high-heeled hotel
guests. The new-age service marketing mix could include meditation pro­
grams, detox programs, fitness programs, healthy diet programs, and sleep
hygiene programs.
As repeat customers, patrons seek in-depth participation in focused activ­
ities while first-time visitors have generalist preferences (Lehto et al., 2004).
Service providers can launch attractive customer loyalty programs with diverse
portfolios of tourist market offerings based on where they figure in the market
opportunity spectrum. Since travel products are usually similar and easy to
replicate, service differentiation through tiered activities tailored to specific
segments (who maybe targeted by harnessing the power of AI and predictive
analytics) will reduce the perceived benefits of switching service providers and
foster a loyal customer base. Further, a pitch focused on image differentiation
centered around ‘credibility and benevolence’ could turn into a unique selling
point.
As proposed by Tseng et al. (2009), repeat tourist cohorts are of greater
worth to accommodation providers by way of average length of stay, greater
spending and focused destination activities. In targeting this price-value con­
scious segment in an e-commerce era characterized by cost transparency,
marketers will have to use the total service cost (inclusive of all allied services
and discounts in addition to the upfront list price) to build competitive
advantage. Their safety concerns can be addressed to an extent by been
securing and homogenizing space for tourism activities. Service providers
engaged in tourism product development can use such information to package
and position their offerings to appeal to this lucrative repeat market. To
support them in this transition, marketers may leverage the power of pre­
dictive analytics and prior consumption data in order to design personalized
products for guests.
It goes without saying that investing in hygiene and cleanliness must be
critical, given the long-term residual effects of the pandemic and guest sensi­
tivity toward the same. The present study revealed that young, value conscious
women travelers tend to be more risk taking and also more brand loyal. While
customers in general are increasingly influenced by hygiene and cleanliness
conditions when making purchase decisions in a service environment (Choi,
2019), young women guests in particular are inclined to pay a premium for
enhanced guest room disinfection (Zhang et al., 2020). Hence, it is time hotels
commit to hygiene protocols and adopt a zero tolerance approach in house­
keeping standards (Hung et al., 2018). To ensure safety of guests and staff,
hoteliers could reassess their service blueprints for possibilities of enabling
artificial intelligence technology (such as voice check-in, AI guided selfservice) at high contact points.
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
29
Conclusion
Despite the worrying performance statistics, much evidence suggests that
COVID-19 will be transformative for sunrise sectors like hospitality. Having
pushed the industry toward an inflexion point, the crisis may redirect the
sector toward a path of transformative growth – embracing inclusivity, sus­
tainability and responsibility. If factors that triggered the urge to travel till now
included globalization, work–life balance and economic well-being, traveler
behavior in the future will be driven by job security, price-value perceptions,
perceived health risks, sensitivity to the ecosystem, responsible consumption
and other pandemic-induced responses. Service providers who understand,
invest and adapt to the language of change are bound to jump the next curve in
adjusting to the new normal.
Limitations and future directions
As the service sector grapples with unprecedented problems, studies such as
this pose relevant, appropriate and timely solutions for business and society.
However, certain limitations that form a basis for future research maybe
noted. For one, the sample size had to be compromised because of the
unconducive time (the initial period of pandemic induced lockdown) in
which the data were collected, owing to which responses were not forthcom­
ing. Researchers were not permitted to to widen the sampling frame due to
newfound issues of privacy and permit expiry induced by the lockdown.
Secondly, this study specifically examines loyalty dimensions in the hotel
industry within the hospitality sector. The replication of this study in
a different business setting is recommended. Further, only selected antece­
dents to customer loyalty were discussed in this study. In order to improve the
predictive power of the model, future research could include wider range of
antecedents like switching costs, customer engagement, value co-creation,
service quality, service recovery strategy, brand resonance, corporate citizen­
ship and brand credibility (Rather & Hollebeek, 2019; Rather et al., 2018; Raza
et al., 2020; Shams et al., 2020; J. U. Islam et al., 2020). Fresh constructs like
consumer orientation (like hedonism or utilitarianism) or new dimensions
like ‘sustainability quotient’ may be incorporated to create a more compre­
hensive research model.
Disclosure statement
On behalf of all authors, the corresponding author states that there is no conflict of interest.
30
D. PAULOSE AND A. SHAKEEL
References
Ali, F., Amin, M., & Cobanoglu, C. (2016). An integrated model of service experience,
emotions, satisfaction, and price acceptance: An empirical analysis in the Chinese hospitality
industry. Journal of Hospitality Marketing & Management, 25(4), 449–475. https://doi.org/
10.1080/19368623.2015.1019172
Babin, B. J., et al, (2005). Modeling consumer satisfaction and word-of-mouth: Restaurant
patronage in Korea. Journal of Services Marketing. Edited by M. Laroche, 19(3), 133–139.
https://doi.org/10.1108/08876040510596803.
Bagozzi, R. P. (1992). The self-regulation of attitudes, intentions, and behavior. Social
Psychology Quarterly, 55(2), 178. https://doi.org/10.2307/2786945
Ball, D., Coelho, P. S., & Vilares, M. J. (2006). Service personalization and loyalty. Journal of
Services Marketing, 20(6), 391–403. https://doi.org/10.1108/08876040610691284
Barron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social
psychology research: Conceptual, strategic, and statistical consideration. Journal of
Personality and Social Psychology51(6), 1173–1182.
Bharadwaj, N., & Matsuno, K. (2006). Investigating the antecedents and outcomes of customer
firm transaction cost savings in a supply chain relationship. Journal of Business Research, 59
(1), 62–72. https://doi.org/10.1016/j.jbusres.2005.03.007
Bloemer, J., de Ruyter, K., & Peters, P. (1998). Investigating drivers of bank loyalty: The
complex relationship between image, service quality and satisfaction. International Journal
of Bank Marketing, 16(7), 276–286. https://doi.org/10.1108/02652329810245984
Byrne, B. M. (2010). Multivariate applications series. Structural equation modeling with AMOS:
Basic concepts, applications, and programming (2nd ed.) ed.). Routledge/Taylor & Francis
Group.
Chang, H., & Wang, H. (2011). The moderating effect of customer perceived value on online
shopping behaviour. Online Information Review, 35(3), 333–359. https://doi.org/10.1108/
14684521111151414
Chang, H. H., Wang, Y. H., & Yang, W. Y. (2009). The impact of e-service quality, customer
satisfaction and loyalty on e-marketing: Moderating effect of perceived value. Total Quality
Management & Business Excellence, 20(4), 423–443. https://doi.org/10.1080/
14783360902781923
Chaudhary, S. & Dey, A.K. (2016). A Confirmatory Factor Analysis of Teenage Consumer
Styles Inventory: Evidence from India. Amity Business Review, 17(1), 31–41
Chen, S. C. (2012). The customer satisfaction–loyalty relation in an interactive e-service setting:
The mediators. Journal of Retailing and Consumer Services, 19(2), 202–210. https://doi.org/
10.1016/j.jretconser.2012.01.001
Choi, J. (2019). Is cleanliness really a reason for consumers to revisit a hotel? Journal of
Environmental Health, 82(5), 16–22.
Cronin, J. J., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and
customer satisfaction on consumer behavioral intentions in service environments. Journal of
Retailing, 76(2), 193–218. https://doi.org/10.1016/S0022-4359(00)00028-2
Czepiel, J. A., Rosenberg, L. J., & Akerele, A. (1974). Perspectives on consumer satisfac­
tion’. Quoted in AMA Educators. Proceedings, Chicago: American Marketing Association,
122, 119-123.
Eggert, A., & Ulaga, W. (2002). Customer perceived value: A substitute for satisfaction in
business markets. The Journal of Business and Industrial Marketing17(2), 107–118.
El-Adly, M. I. (2019). Modelling the relationship between hotel perceived value, customer
satisfaction, and customer loyalty. Journal of Retailing and Consumer Services, 50, 322–332.
https://doi.org/10.1016/j.jretconser.2018.07.007
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
31
Frías Jamilena, D. M., & Rodríguez Molina, M. Á. (2013). Antecedents of loyalty toward rural
hospitality enterprises: The moderating effect of the customer’s previous experience.
International Journal of Hospitality Management, 34(1), 127–137. https://doi.org/10.1016/j.
ijhm.2013.02.011
Gallarza, M. G., Saura, I. G. (2006). Value dimensions, perceived value, satisfaction and loyalty:
an investigation of university students’ travel behaviour. Tourism Management27(3), 437–
452.
Goh, E., & Okumus, F. (2020). Avoiding the hospitality workforce bubble: Strategies to attract
and retain generation Z talent in the hospitality workforce. Tourism Management
Perspectives, 33(1). https://doi.org/10.1016/j.tmp.2019.100603
Gossling, S., Scott, D., & Hall, C. M. (2020). Pandemics, tourism and global change: A rapid
assessment of COVID-19. Journal of Sustainable Tourism, 29(5),1–20. 1–20. https://doi.org/
10.1080/09669582.2020.1758708
Griffin, J. (2010). Customer loyalty: How to earn it, how to keep it (New and rev ed.). Jossey-Bass
(The Jossey-Bass business & management series).
Gronholdt, L., Martensen, A., & Kristensen, K. (2000). The relationship between customer
satisfaction and loyalty: Cross-industry differences. Total Quality Management, 11(4–6),
509–514. https://doi.org/10.1080/09544120050007823
Gupta, S., McLaughlin, E., & Gomez, M. (2007). Guest satisfaction and restaurant performance.
Cornell Hotel and Restaurant Administration Quarterly, 48(3), 284–298. https://doi.org/10.
1177/0010880407301735
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis.
Englewood Cliff5(3), 207–2019.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data
analysis New Jersey: Pearson Education.
Hanan, M. & Karp, P. (1989). Customer Satisfaction: How to MaximizeMeasureand Market
Your Company’s Ultimate Product. American Management Association, New York.
Hanefors, M. & Mossberg, L. (2003). Searching for the extraordinary meal experience. Journal
of Business and Management9(3), 249–270.
Heung, V. C. S., & Ngai, E. W. T. (2008). The mediating effects of perceived value and customer
satisfaction on customer loyalty in the Chinese restaurant setting. Journal of Quality
Assurance in Hospitality & Tourism, 9(2), 85–107. https://doi.org/10.1080/
15280080802235441
Hollebeek, L. D. (2011). Demystifying customer brand engagement: Exploring the loyalty
nexus. Journal of Marketing Management, 27(7–8), 785–807. https://doi.org/10.1080/
0267257X.2010.500132
Hollebeek, L. D., & Rather, R. A. (2019). Service innovativeness and tourism customer
outcomes. International Journal of Contemporary Hospitality Management, 31(11),
4227–4246. https://doi.org/10.1108/IJCHM-03-2018-0256
Hollebeek, L. D., Sprott, D. E., Andreassen, T. W., Costley, C., Klaus, P., Kuppelwieser, V.,
Karahasanovic, A., Taguchi, T., Ul Islam, J., & Rather, R. A. (2019). Customer engagement in
evolving technological environments: Synopsis and guiding propositions. European Journal
of Marketing, 53(9), 2018–2023. https://doi.org/10.1108/EJM-09-2019-970
Hollebeek, L. D., Sprott, D. E., Andreassen, T. W., Costley, C., Klaus, P., Kuppelwieser, V., &
Rather, R. A. (2017). Customer engagement in evolving technological environments:
Synopsis and guiding propositions. European Journal of Marketing53(9), 2018–2023.
Hsu, H. (2006). An empirical study of web site quality, customer value, and customer satisfac­
tion based on e-shopping. The Business Review5(1), 190–193.
Hung, K. K. C., Mark, C. K. M., Yeung, M. P. S., Chan, E. Y. Y., & Graham, C. A. (2018). The
role of the hotel industry in the response to emerging epidemics: A case study of SARS in
32
D. PAULOSE AND A. SHAKEEL
2003 and H1N1 swine flu in 2009 in Hong Kong. Globalization and Health, 14(1), 117.
https://doi.org/10.1186/s12992-018-0438-6
Ishaq, M. I., Hussain, N. M., Asim, A. I. & Cheema, L.J. (2014). Brand Equity in the Pakistani
Hotel Industry. RAE - Revista de Administração de Empresas, 54(3), 235–260.
Islam, J. U., Shahid, S., Rasool, A., Rahman, Z., Khan, I., & Rather, A. R. (2020). Impact of
website attributes on customer engagement in banking: A solicitation of stimulus-organismresponse theory. International Journal of Bank Marketing, 38(6), 1279-1303 0265-2323,
https://doi.org/10.1108/IJBM-12-2019-0460.
Islam, U. I., Hollebeek, L. D., Rahman, Z., Khan, I., & Rasool, A. (2019). Customer engagement
in the service context: An empirical investigation of the construct, its antecedents and
consequences. Journal of Retailing and Consumer Services, 50(1), 277–285. https://doi.org/
10.1016/j.jretconser.2019.05.018
Jiang, Y., & Wen, J. (2020). Effects of COVID-19 on hotel marketing and management:
A perspective article. International Journal of Contemporary Hospitality Management, 32
(8), 2563–2573. https://doi.org/10.1108/IJCHM-03-2020-0237
Johar, J. S. & Sirgy, M. J. (1991). Value-expressive versus utilitarian advertising appeals: When
and why to use which appeal. Journal of advertising, 20(3), pp. 23–33.
Jones, H., & Farquhar, J. D. (2003). Contact management and customer loyalty. Journal of
Financial Services Marketing, 8(1), 71–78. https://doi.org/10.1057/palgrave.fsm.4770108
Josiam, B. M., Smeaton, G., & Clements, C. J. (2000). Involvement: Travel motivation and
destination selection. Journal of Vacation Marketing, 5(2), 167–175. https://doi.org/10.1177/
135676679900500205
Kandampully, J., & Suhartanto, D. (2003). An examination of the relationship between
customer loyalty, customer satisfaction, and image in the hotel industry. International
Journal of Contemporary Hospitality Management, 12(6), 346–351. https://doi.org/10.1108/
09596110010342559
Kandampully, J., Zhang, T., & Bilgihan, A. (2015). Customer loyalty: A review and future
directions with a special focus on the hospitality industry. International Journal of
Contemporary Hospitality Management, 27(3), 379–414. https://doi.org/10.1108/IJCHM03-2014-0151
Kesari, B., & Atulkar, S. (2016). Satisfaction of mall shoppers: A study on perceived utilitarian
and hedonic shopping values. Journal of Retailing and Consumer Services, 31, 22–31. https://
doi.org/10.1016/j.jretconser.2016.03.005
Konuk, F. A. (2019). The influence of perceived food quality, price fairness, perceived value and
satisfaction on customers’ revisit and word-of-mouth intentions towards organic food
restaurants. Journal of Retailing and Consumer Services, 50(4), 103–110. https://doi.org/10.
1016/j.jretconser.2019.05.005
Kotler, P. (2003). Marketing management (7th ed., pp. 123–192). Prentice Hall.
Kuo, N. T. (2013). how service quality affects customer loyalty in the travel agency: The effects
of customer satisfaction, service recovery, and perceived value. Asia Pacific Journal of
Tourism Research, 18(7), 803–822. https://doi.org/10.1080/10941665.2012.708352
Lapointe, D. (2020). Reconnecting tourism after COVID-19: The paradox of alterity in tourism
areas. Tourism Geographies, 22(3), 633–638. https://doi.org/10.1080/14616688.2020.1762115
Leckie, C., Nyadzayo, M. W., & Johnson, L. W. (2016). Antecedents of consumer brand
engagement and brand loyalty. Journal of Marketing Management, 32(5–6), 558–578.
https://doi.org/10.1080/0267257X.2015.1131735
Lee, C.-K., Yoon, Y.-S., & Lee, S.-K. (2007). Investigating the relationships among perceived
value, satisfaction, and recommendations: The case of the Korean DMZ. Tourism
Management, 28(1), 204–214. https://doi.org/10.1016/j.tourman.2005.12.017
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
33
Lehto, X. Y., O’Leary, J. T., & Morrison, A. M. (2004). The effect of prior experience on
vacation behavior. Annals of Tourism Research, 31(4), 801–818. https://doi.org/10.1016/j.
annals.2004.02.006
Lin, Y. H. (2015). Innovative brand experience’s influence on brand equity and brand satisfac­
tion. Journal of Business Research, 68(11), 2254–2259. https://doi.org/10.1016/j.jbusres.2015.
06.007
Lock, S. (2020). Tourism worldwide - Statistics & Facts. Retrieved from May 2, 2020 https://
www.statista.com/topics/962/global-tourism/
Mathwick, C., Malhotra, N., & Rigdon, E. (2001). Experiential value: Conceptualization,
measurement and application in the catalog and Internet shopping environment. Journal
of Retailing, 77(1), 39-56..
McDougall, G. H., & Levesque, T. (2000). Customer satisfaction with services: Putting per­
ceived value into the equation. Journal of services marketing, 14(5), 392–410.
Ministry of tourism (2020). India tourism statistics. the Ministry of Tourism, Government of
India. Retrieved from http://tourism.gov.in/market-research-and-statistics
Mittal, B., & Lassar, W. (1998). Why do customers switch? The dynamics of satisfaction versus
loyalty. Journal of Services Marketing, 12(3), 177–194. https://doi.org/10.1108/
08876049810219502
Morais, D. B., & Lin, C.-H. (2010). Why do first-time and repeat visitors patronize a
destination? Journal of Travel & Tourism Marketing, 27(2), 193–210. https://doi.org/10.
1080/10548401003590443
Narteh, B., Agbemabiese, G. C., Kodua, P., & Braimah, M. (2013). Relationship marketing and
customer loyalty: evidence from the Ghanaian luxury hotel industry. Journal of Hospitality
Marketing & Management, 22(4), 407–436. https://doi.org/10.1080/19368623.2012.660564
Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63(4_suppl1), 33–44.
https://doi.org/10.1177/00222429990634s105
Pham, T. H., & Huang, -Y.-Y. (2015). The impact of experiential marketing on customer’s
experiential value and satisfaction: An empirical study in Vietnam hotel sector. Journal of
Business Management, 4(2319), 19.
Prahalad, C. K., & Ramaswamy, V. (2000). Co-opting customer competence. Harvard Business
Review, 78(1), 79–87.
Pullman, M. E. & Gross, M. A. (2004). Ability of experience design elements to elicit emotions
and loyalty behaviours. Decision Science, 35(3), 551–578.
Rather, R. A. (2018). Investigating the Impact of customer brand identification on hospitality
brand loyalty: A social identity perspective. Journal of Hospitality Marketing & Management,
27(5), 487–513. https://doi.org/10.1080/19368623.2018.1404539
Rather, R. A. (2019). Consequences of consumer engagement in service marketing: An
empirical exploration. Journal of Global Marketing, 32(2), 116–135. https://doi.org/10.
1080/08911762.2018.1454995
Rather, R. A. (2020). Customer experience and engagement in tourism destinations: The
experiential marketing perspective. Journal of Travel & Tourism Marketing, 37(1), 15–32.
https://doi.org/10.1080/10548408.2019.1686101
Rather, R. A., & Camilleri, M. A. (2020). The customers’ brand identification with luxury
hotels: A social identity perspective. In F. Pantoja, S. Wu, & N. Krey (Eds.), Enlightened
marketing in challenging times (pp. 429–443). Springer International Publishing. https://doi.
org/10.1007/978-3-030-42545-6_141
Rather, R. A., & Camilleri, M. A. (2019). The effects of service quality and consumer-brand
value congruity on hospitality brand loyalty. Anatolia, 30(4), 547–559. https://doi.org/10.
1080/13032917.2019.1650289
34
D. PAULOSE AND A. SHAKEEL
Rather, R. A., & Hollebeek, L. D. (2019). Exploring and validating social identification and
social exchange-based drivers of hospitality customer loyalty. International Journal of
Contemporary Hospitality Management, 31(3), 1432–1451. https://doi.org/10.1108/
IJCHM-10-2017-0627
Rather, R. A., & Hollebeek, L. D. (2020). Experiential marketing for tourism destinations. In
The Routledge handbook of tourism experience management and marketing. edited by
Saurabh Kumar Dixit, Routledge Publications, NY.
Rather, R. A., Hollebeek, L. D., & Islam, J. U. (2019a). Tourism based customer engagement:
The construct, antecedents, and consequences. The Service Industries Journal, 39(7–8),
519–540. https://doi.org/10.1080/02642069.2019.1570154
Rather, R. A., & Sharma, J. (2019). Dimensionality and consequences of customer engagement:
A social exchange perspective. Vision: The Journal of Business Perspective, 23(3), 255–266.
https://doi.org/10.1177/0972262919850923
Rather, R. A., Tehseen, S., Itoo, M. H., & Parrey, S. H. (2019b). Customer brand identification,
affective commitment, customer satisfaction, and brand trust as antecedents of customer
behavioral intention of loyalty: An empirical study in the hospitality sector. Journal of Global
Scholars of Marketing Science, 29(2), 196–217. https://doi.org/10.1080/21639159.2019.
1577694
Rather, R. A., Tehseen, S., & Parrey, S. H. (2018). Promoting customer brand engagement and
brand loyalty through customer brand identification and value congruity. Spanish Journal of
Marketing - ESIC, 22(3), 319–337. https://doi.org/10.1108/SJME-06-2018-0030
Raza, A., Rather, R. A., Iqbal, M. K., & Bhutta, U. S. (2020). An assessment of corporate social
responsibility on customer company identification and loyalty in banking industry: A
PLS-SEM analysis. Management Research Review, 43(11), 1337–1370. https://doi.org/10.
1108/MRR-08-2019-0341
Reicheld, F. F. & Sasser, W. E. Jr.(1990). Zero defections comes to services, Harvard Business
Review, 68(3), 105–111.
Ryu, K., Lee, H., & Gon Kim, W. (2012). The influence of the quality of the physical environ­
ment, food, and service on restaurant image, customer perceived value, customer satisfac­
tion, and behavioral intentions. International Journal of Contemporary Hospitality
Management, 24(2), 200–223. https://doi.org/10.1108/09596111211206141
Sahoo, D., & Ghosh, T. (2016). Healthscape role towards customer satisfaction in private
healthcare. International Journal of Health Care Quality Assurance, 29(6), 600–613.
https://doi.org/10.1108/IJHCQA-05-2015-0068.
Schmitt, B. (1999). Experiential Marketing. Journal of Marketing Management, 15(1–3), 53–67.
https://doi.org/10.1362/026725799784870496
See-To, E. W. K., & Ho, K. K. W. (2014). Value co-creation and purchase intention in social
network sites: The role of electronic Word-of-Mouth and trust – A theoretical analysis.
Computers in Human Behavior, 31(1), 182–189. https://doi.org/10.1016/j.chb.2013.10.013
Shams, G., Rather, R., Abdul Rehman, M., & Lodhi, R. N. (2020). Hospitality-based service
recovery, outcome favourability, satisfaction with service recovery and consequent customer
loyalty: An empirical analysis. International Journal of Culture, Tourism and Hospitality
Research, ahead-of-print(ahead–of–print), ahead-of-print. https://doi.org/10.1108/IJCTHR04-2020-0079.
Sharma, P. (2011). Country of origin effects in developed and emerging markets: Exploring the
contrasting roles of materialism and value consciousness. Journal of International Business
Studies, 42(2), 285–306. https://doi.org/10.1057/jibs.2010.16
Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational
exchanges. Journal of Marketing, 66(1), 15–37. https://doi.org/10.1509/jmkg.66.1.15.18449
JOURNAL OF QUALITY ASSURANCE IN HOSPITALITY & TOURISM
35
Smilansky, S. (2009). Experiential Marketing: A practical guide to interactive brand
experiences. Kogan Page, 9–16.
Statista Market Forecast. (2019). Hotels – Worldwide. Retrieved May 2, 2020 from https://www.
statista.com/outlook/267/100/hotels/worldwide
Tarun, K. S., & Chopra, S. L. (2007). Beyond the retail hype. Indian Management, 46(1), 12–27.
Teich, I. (1997). Holding on to customers: the bottom-line benefits of relationship building.
Bank Marketing, 29(2),pp. 12–18.
Tseng, M. & Lan, L. W., Lin, K., Chang, C. & Lin, Z. (2009). Application of Experiential
Marketing Strategy to Identify Factors Affecting Guests'Leisure Behaviour in Taiwan HotSpring Hotel. WSEAS transactions on Business and Economics, 6(5), 252–301.
Twenge, J. M. (2010). A review of the empirical evidence on generational differences in work
attitudes. Journal of Business and Psychology, 25(2), 201–210.
Wilkins, H., Merrilees, B., & Herington, C. (2007). Towards an understanding of total service
quality in hotels. International Journal of Hospitality Management, 26(4), 840–853. https://
doi.org/10.1016/j.ijhm.2006.07.006
Wong, A. (2004). The role of emotional satisfaction in service encounters. Managing Service
Quality: An International Journal, 14(5), 365–376. https://doi.org/10.1108/
09604520410557976
Yang, Z. & Peterson, R. T. (2004). Customer Perceived Value, Satisfaction and Loyalty: The
Role of Switching Costs. Psychology & Marketing, 21(10), 799–822.
Zhang, S., Diao, M., Yu, W., Pei, L., Lin, Z., & Chen, D. (2020). Estimation of the reproductive
number of novel coronavirus (COVID-19) and the probable outbreak size on the Diamond
Princess cruise ship: A data-driven analysis. International Journal of Infectious Diseases, 93
(1), 201–204. https://doi.org/10.1016/j.ijid.2020.02.033