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The effect of price on return intentions:
Do satisfaction and reward programme
membership matter?
Breffni M. Noonen and Daniel J. Mount
Received (in revised form): 3rd April, 2007
n
School of Hospitality Management, The Pennsylvania State University, 215 Mateer Building, University Park,
PA 16802-1307, USA
Tel: þ 1 814 865 7128; Fax: þ 1 814 863 4257; E-mail: [email protected]
Breffni M. Noone is an assistant professor of
operations management in the School of
Hospitality Management at the Pennsylvania
State University. She earned her doctorate
from Cornell University. Her research interests
include pricing, forecasting and distribution
channel management in the hotel and restaurant industries. Currently she is studying
customer reaction to demand-based pricing
and related revenue management practices.
Daniel J. Mount is an associate professor
of hospitality management in the School of
Hospitality Management at the Pennsylvania
State University. He earned his doctorate from
Alliant International University. His research
interests include service management and the
impact of quality and quality processes on
satisfaction in the lodging industries.
ABSTRACT
KEYWORDS: price, customer satisfaction,
reward programme, return intentions
The purpose of this study was to examine the effect of
price on customers’ return intentions. Specifically, we
looked at the moderating influence of satisfaction and
reward programme membership on the relationship
between price and return intent. Hierarchical multiple
regression, using data drawn from the survey database
of a major hotel chain, was employed to test hypotheses.
Results for the leisure customer segment indicate that,
regardless of customers’ satisfaction levels with a given
service experience, the price paid for that experience has
a direct, negative effect on return intent. Furthermore,
reward programme membership does not negate the
negative effect of price on customers’ intent to repatronise
a service provider.
Journal of Revenue and Pricing Management
(2008) 7, 357–369. doi:10.1057/rpm.2008.21
published online 27 June 2008
INTRODUCTION
Research has shown that increases in customer
retention result in increased profitability for
firms that compete in mature, competitive
markets; a characteristic true of a number
of service industries that practice revenue
management including hotels, airlines and
telecommunications (Varki and Colgate, 2001).
This increased profitability results from
increased consumption by existing customers,
lower costs of retention, the generation of new
business via word-of-mouth recommendations
and the engagement of fewer resources in the
satisfaction of existing customer needs (Bolton,
1998; Rust et al., 1995). Research has shown
that service quality (Bitner, 1990; Boulding et
al., 1993), relationship quality (Crosby and
Stephens, 1987; Crosby et al., 1990) and overall
service satisfaction (Cronin and Taylor, 1992)
can improve customers’ intentions to repatronise a firm. However, can price cause service
firms that practice revenue management to lose
& 2008 Palgrave Macmillan, 1476-6930 Vol. 7, 4 357–369 Journal of Revenue and Pricing Management
357
Effect of price on return intentions
customers? The use of demand-based pricing
in revenue management dictates that, during
periods of high demand, lower rates will be
closed in order to maximise revenue. While
this approach to pricing can yield short-term
revenue gains, could customer retention rates,
and by extension long-term revenue, be
negatively impacted by customers’ reactions to
the price that they have to pay?
Consider the customer who wants a hotel
room in New York City on a given weekend.
He ends up paying a high rate for a hotel room
because citywide demand is high. While he is
not very happy about the rate, he pays it in
order to spend the weekend in the city. He
subsequently stays in the hotel and is very
satisfied with the experience. Will the high rate
that he was charged deter him from staying in
that hotel on a subsequent visit to the city or
will his satisfaction with his stay override his
discontent with the rate and positively impact
his willingness to repatronise the hotel?
Given the potential of customer retention to
boost profitability, it is critical that revenue
managers understand the impact of price on
customer repurchase intentions so that they can
develop pricing strategies that foster customer
retention. Therefore, in this study we seek to
complement previous research on customers’
perceptions of revenue management pricing by
examining the effect that actual price can have
on customers’ return intentions. Specifically,
we will examine the moderating effect of
satisfaction on the relationship between price
and return intentions: does satisfaction with a
service experience weaken the effect of price
on return intentions? Additionally, we examine
the effect of reward programme membership
on the price–return intent relationship. Does
membership of such programmes sufficiently
raise perceived switching costs to negate any
negative effect that price may have on return
intentions?
The structure of this paper is as follows.
First, the literature relevant to the research
hypotheses is reviewed. A description of the
research methodology and empirical results are
358
then presented. The paper concludes with a
discussion of the implications of the findings
for management practice and future research.
CONCEPTUAL BACKGROUND
Pricing is a key strategic lever used by firms to
manage revenue (Kimes and Chase, 1998). A
variable pricing structure allows for the use of
discounted rates to stimulate demand for
inventory that would otherwise go unsold
(see eg, Hanks et al. (1992) for a discussion of
demand-based pricing and related rate fences).
In the revenue management literature customer
reaction to pricing has been examined primarily from a fairness perspective. Customers’
perceptions of the fairness of revenue management pricing and related rate fences have been
found to be affected by the amount of
information disclosed to customers (Kimes,
1994; Choi and Mattila, 2003), the framing of
prices, with customers perceiving economically
equivalent pricing schedules as fairer when they
are framed as discounts rather than surcharges
(Kimes and Wirtz, 2003), and familiarity with
revenue management pricing practices (Wirtz
and Kimes, 2007). Customers’ perceptions of
price fairness have also been examined in the
mainstream marketing literature (eg Thaler,
1985; Kahneman et al., 1986; Campbell, 1999;
Xia et al., 2004). In a related stream of research,
a number of authors have examined the effect
of perceived price on perceived quality (eg Rao
and Monroe, 1989; Teas and Agarwal, 2000),
perceived value (eg Zeithaml, 1988; Bolton
and Drew, 1991; Cronin et al., 2000; DeSarbo
et al., 2001; Woodruff, 1997; Ng, 2008) and
satisfaction (eg Fornell et al., 1996; Voss et al.,
1998; Bolton and Lemon, 1999). Unfavourable
price perceptions have also been found to have
a direct negative effect on behavioural intentions (eg Dodds et al., 1991; Varki and Colgate,
2001).
Customers’ reactions to actual prices have
also been examined in the literature. Studies by
Bolton and Lemon (1999) and Mattila and
O’Neill (2003) have found that actual price
has a significant effect on overall customer
Journal of Revenue and Pricing Management Vol. 7, 4 357–369 & 2008 Palgrave Macmillan, 1476-6930
Noone and Mount
satisfaction. Homburg et al. (2005) examined
the effect of price increases on return intentions
and found that satisfaction prior to a price
increase moderates the effect of the magnitude
of a price increase on repurchase intentions. In
this study we are interested in the effect of the
actual price encountered for a specific service
experience on future repurchase intentions and
the potential moderating effect of post-consumption satisfaction with that service experience on the relationship between price and
repurchase intent. Keaveney (1995) identified
price as one of the main causal variables for
customer switching from one service provider
to another. Within price, the study revealed
four subcategories that drive customer switching: (1) the price being too high relative to
some internal reference price, (2) price increases, (3) unfair pricing practices and (4)
deceptive pricing practices. Keaveney (1995)
found that, even when satisfied with their
former providers, customers switched providers
due to price. Building on the notion that
satisfied customers will switch service providers
due to price, we propose that, in the context of
services where demand-based pricing is applied, price will remain a significant determinant of customers’ return intentions over and
above their satisfaction with the service. The
product-service offering has become increasingly commoditised for services using demandbased pricing such as hotels and airlines. As a
result, customers often seek the ‘best’ (lowest)
price across, what they perceive as, similar
offerings. Therefore, we propose:
H1: Satisfaction does not moderate the effect of
price on return intentions. Regardless of satisfaction levels, price has a direct negative effect on
customers’ return intentions.
Customer loyalty has been identified as the key
to success in a commoditised environment
(Mattila, 2006). To that end, many service
firms that employ revenue management attempt to foster customers’ loyalty by offering
frequent-guest, or reward, programmes, with
rewards that include hard benefits (eg free
stays/flights) and soft benefits (eg priority
check-in). Such programmes are designed to
raise perceived switching costs and keep
customers from switching to a competing
brand (Sharp and Sharp, 1997). However, it
has been argued that the accumulation of
frequency points — and the rewards stemming
from those points — is not sufficient to create
loyalty (Mattila, 2006). Commitment, which
can be defined as an enduring desire to
maintain a valued relationship (Moorman
et al., 1992), has been identified as the key
concept in any relationship that involves loyalty
(Dwyer et al., 1987; Wetzels et al., 2001).
Commitment consists of two dimensions:
affective commitment and calculative commitment (Gruen et al., 2000; Gilliland and Bello,
2002). Calculative commitment refers to a
customer’s need or desire to maintain a
relationship in face of high switching costs.
As such, reward programmes can be viewed as
reflecting a calculative commitment (Mattila,
2006). Affective commitment, on the other
hand, reflects a customer’s emotional attachment to the service provider or brand. Affective
commitment has been shown to be an
important predictor of behavioural loyalty. For
example, Mattila (2006) found that customers
with high affective commitment to a brand
were more likely to consider that brand as their
first choice and promote the brand among their
friends and colleagues. Affective commitment
also resulted in a bigger share of the customer’s
wallet, as indicated by a higher percentage of
room-nights allocated to the preferred brand.
Conversely, ‘dependency’ or point accumulation was not a major determinant of behavioural loyalty (Mattila, 2006). In a similar vein,
Gilliland and Bello (2002) note that, while
calculative commitment indicates an attachment, customers would be willing to terminate
the relationship with a service provider should
they receive an economically superior offer
from another.
For services using demand-based pricing
such as hotels and airlines, the similarity of
& 2008 Palgrave Macmillan, 1476-6930 Vol. 7, 4 357–369 Journal of Revenue and Pricing Management
359
Effect of price on return intentions
Satisfaction
Table 1: Description of hotel brands
n.s.
Price
Return Intentions
n.s.
Hotel brand
Descriptiona
Full-service
Brand of quality-tier, full-service
hotels: features include food and
beverage facilities, meeting
facilities and business centres and
recreation facilities
Reward Program
Membership
n.s. = not significant
Figure 1: Proposed model of the role of satisfaction
and reward programme membership in the price–
return intentions relationship
rewards within different companies’ programmes, coupled with the typical traveller
holding membership of multiple reward programmes, makes it easy to switch service
providers in pursuit of the ‘best deal’(Mattila,
2006). Given this, coupled with the findings of
Mattila (2006) regarding the relationship between point accumulation and behavioural
loyalty, we posit that membership of a given
reward programme is not sufficient to override
the effect of price on customers’ return
intentions. Specifically, we hypothesise:
H2: Reward programme membership does not
moderate the negative effect of price on return
intent.
See Figure 1 for a graphical representation of
H1 and H2.
Limited-service Moderately priced limited-service
brand: provides more limited guest
services than the full service brand
Mid-scale
Moderately priced all-suite brand:
no restaurant or meeting facilities
Economy
Consistent, affordable lodging: no
restaurant or meeting facilities,
limited recreational amenities
Boutique
Quality-tier, full-service brand:
distinguished by their level of
personalised service and individual
style
Extended stay: Mid-priced extended stay brand:
mid-scale
designed for guests staying five or
more nights
Extended stay: Economy-priced extended stay
economy
brand: more limited guest services
than the mid-scale extended stay
brand
a
THE STUDY
Hypotheses were tested using a survey database
from a major hotel chain that practises revenue
management. The advantages of using this data
set were threefold. First, it contained information on the specific variables of interest in this
study. Specifically, it included customers’ selfreported evaluative assessments of their hotel
stay, in addition to actual data relating to the
room rate paid by customers, their reward
programme status and booking information.1
The database also provided us access to data
relating to guest stays from seven diverse
brands (full service, limited service, mid-scale,
360
The descriptions provided in this table are those
used by the hotel chain to describe their brands
economy, boutique and extended stay (midscale and economy) brands), which enabled us
to test the robustness of our results across hotel
type. See Table 1 for descriptions of hotel
brands. Secondly, the data set represented
behaviours and reactions of real customers in
a real service environment and was not limited
to reported attitudes or reactions, as is the
case with an experimental design (Winer,
1999). Thirdly, use of this data set afforded us
Journal of Revenue and Pricing Management Vol. 7, 4 357–369 & 2008 Palgrave Macmillan, 1476-6930
Noone and Mount
cost-efficient access to a larger sample size than
an in-person survey approach.
However, the limitation of using data
collected in this manner is that we were
confined to the measures that were employed
by the hotel chain to collect that data.
Specifically, we were limited to single-item
measures of the constructs that were of interest
to us. These included a global measure of guest
satisfaction (1 ¼ poor, 10 ¼ excellent), service
quality (1 ¼ poor, 10 ¼ excellent) and intent to
return to the brand (1 ¼ definitely not,
5 ¼ definitely will). However, there is precedence in the academic literature for the use of
single-item measures. Finn and Kayande (1997)
have argued in favour of overall measures as
being reliable as respondents are better able to
make aggregate judgments.
The data sample used in this study was
drawn from the company’s March 2005 records
relating to guests’ stays during that month. This
timeframe was considered appropriate as it
included both high and low demand periods
across all of the brands. As a result, we were
able to capture significant variability in price
across the data set. See Table 2 for summary
room rate data by brand. Given our interest in
the relationship between price and return
intentions, we included only the data from
the leisure customer segment (identified as
customers who selected leisure as their purpose
of stay) in our analysis. Our rationale for
excluding business customers (identified as
customers who selected business as their
purpose of stay) was that there may be more
likelihood of repurchase among these customers by virtue of negotiated room rates and/or
company policy. Since the hotel’s database did
not include information that would allow us to
control for this factor, we excluded the business
customer segment from our analysis. Therefore, in total, data from 1,745 customers were
included in the study, with an approximately
equal number of observations from each of
the seven brands. Of the respondents,
47.5 per cent (N ¼ 829) were female. In terms
of reward programme membership, 75 per cent
(N ¼ 1309) of respondents were programme
members. Of the respondents, 50.3 per cent
(N ¼ 878) had spent between one and nine
nights in a hotel for leisure purposes over the
12 months prior to completing the survey, with
36.1 per cent (N ¼ 630) spending between ten
and 24 nights and 13.6 per cent (N ¼ 237)
spending more than 24 nights. Rates paid by
respondents ranged from $40 to $411, with an
overall mean of $103.95 (SD ¼ $48.02).
RESULTS
Intent to return to the brand was the
dependent variable in a hierarchical linear
regression. Our rationale for examining return
intent at the brand level as opposed to the hotel
level was that we wanted to test the effect of
Table 2: Room rate data by brand
Brand
N
Full-service
Limited-service
Mid-scale
Economy
Boutique
Extended stay mid-scale
Extended stay economy
262
256
286
243
249
222
227
Room rate
Maximum
Minimum
Mean
Std. deviation
$329.00
$298.00
$269.00
$169.00
$411.00
$265.00
$159.00
$40.00
$44.00
$46.55
$42.00
$40.00
$49.00
$42.00
$129.02
$102.61
$90.82
$73.01
$128.81
$119.56
$83.69
$61.98
$42.49
$24.73
$20.16
$63.63
$40.56
$24.40
& 2008 Palgrave Macmillan, 1476-6930 Vol. 7, 4 357–369 Journal of Revenue and Pricing Management
361
Effect of price on return intentions
price on the broader level of the brand as
opposed to an individual hotel which could be
influenced by customers’ intentions to return
to a specific location again. Room rate, overall
guest satisfaction, reward programme membership status (reward programme member or
nonmember, with members entered in the
regression as the reference group) and their
interaction terms were used as the predictor
variables. Given their potential to influence
customers’ return intentions, the following
were controlled for in the analysis: (1) service
quality evaluation scores, (2) brand (full
service, limited service, mid-scale, economy,
boutique, mid-scale extended stay and
economy extended stay) and (3) frequency of
leisure nights in hotels over the 12 months
prior to survey completion (1–9, 10–24
and more than 24). The results are shown
in Table 3.
Table 3: Hierarchical multiple regression analysis for intent to return to the brand
Independent variables
Step 1
Control variables
Service quality
Hotel branda
Limited service
Mid-scale
Economy
Boutique
Mid-scale extended stay
Economy extended stay
Frequency of leisure nightsb
0–9
10–24
Main effects
Room rate
Satisfaction
Reward programme statusc
Nonmember
Step 2
Control variables
Service quality
Hotel branda
Limited service
Mid-scale
Economy
Boutique
Mid-scale extended stay
Economy extended stay
Frequency of leisure nightsb
0–9
10–24
362
b
Standard error
t-value
0.07
0.01
5.48*
0.01
0.15
0.07
0.06
0.06
0.21
0.07
0.06
0.07
0.07
0.06
0.07
0.03
2.26***
1.05
0.88
0.99
3.01*
0.08
0.04
0.06
0.07
1.29
0.59
0.00
0.29
0.00
0.02
2.69**
19.54*
0.03
0.04
0.78
0.07
0.01
5.48*
0.01
0.15
0.07
0.06
0.06
0.21
0.07
0.06
0.07
0.07
0.06
0.07
0.03
2.26***
1.05
0.88
0.99
3.01*
0.08
0.04
0.06
0.07
1.29
0.6
Journal of Revenue and Pricing Management Vol. 7, 4 357–369 & 2008 Palgrave Macmillan, 1476-6930
Noone and Mount
Table 3: continued
Independent variables
Main effects
Room rate
Satisfaction
Reward programme statusc
Nonmember
Rate satisfaction
b
Standard error
t-value
0.00
0.29
0.00
0.02
0.57
19.50*
0.03
0.04
0.79
0.00
0.00
0.05
0.07
0.01
5.50*
0.01
0.15
0.07
0.06
0.07
0.21
0.07
0.06
0.07
0.07
0.07
0.07
0.02
2.31***
1.00
0.85
1.04
3.06*
0.08
0.04
0.06
0.07
1.29
0.57
0.00
0.29
0.00
0.02
0.75
19.52*
0.03
0.04
0.82
0.00
0.00
0.00
0.00
0.17
0.93
R2 change=0.00
Step 3
Control variables
Service quality
Hotel branda
Limited service
Mid-scale
Economy
Boutique
Mid-scale extended stay
Economy extended stay
Frequency of leisure nightsb
0–9
10–24
Main effects
Room rate
Satisfaction
Reward programme statusc
Nonmember
Rate satisfaction
Rate nonmember
R2 change=0.00
a
The full-service hotel brand was used as the reference group in the regression
The ‘more than 24 nights’ category was used as the reference group in the regression
c
The reward member category was used as the reference group in the regression
*po0.005, **po0.01, ***po0.05
b
Room rate, overall guest satisfaction, reward
programme membership status and the control
variables were entered first into the model
(R2 ¼ 0.443, F ¼ 107.94, po0.01). Having
controlled for service quality evaluations, brand
and frequency of leisure nights, the main effects
for room rate and satisfaction were significant
(Room rate: t ¼ 2.69, po0.01; Satisfaction:
& 2008 Palgrave Macmillan, 1476-6930 Vol. 7, 4 357–369 Journal of Revenue and Pricing Management
363
Effect of price on return intentions
t ¼ 19.54, po0.005), indicating that both room
rate and satisfaction with the hotel stay have a
direct effect on return intentions. The main
effect for reward programme membership was
insignificant (t ¼ 0.78, p>0.1), indicating that
reward programme membership does not
directly affect respondents’ intentions to return
to the brand.
To test the moderating effect of satisfaction
on the price–return intentions relationship, the
interaction term for room rate and satisfaction
was then added to the model. A test of the
difference between the R2 for the model
without the interaction term and the model
with the interaction term was insignificant (R2
change ¼ 0.00, F change ¼ 0.01, p>0.1), indicating that overall satisfaction with the hotel
stay did not moderate the negative effect of
room rate on intent to return to the brand.
Hypothesis 1 is therefore supported.
In the final step, we tested for the moderating effect of reward programme membership
on the price–return intentions relationship
by adding the interaction term for room
rate and reward programme membership to
the model. A test of the difference between
the R2 for the model without the interaction
term and the model with the interaction
term was insignificant (R2 change ¼ 0.00, F
change ¼ 0.88, p>0.1), indicating that reward
programme membership did not moderate
the effect of room rate on intent to return
to the brand. This provides support for
Hypothesis 2.
Furthermore, we conducted an analysis of
the data subset containing reward programme
members only to investigate whether there was
a differential effect of price on return intent
within reward club membership (ie elite versus
nonelite status). A test of the difference
between the R2 for the model without the
reward programme status–price interaction
term and the model with the interaction term
was insignificant (R2 change ¼ 0.00, F
change ¼ 0.05, p>0.1). Regardless of reward
programme status, elite or nonelite, price
directly and negatively affected return intent.
364
DISCUSSION
The focus of the revenue management literature on pricing has been on customers’
perceptions of the fairness of demand-based
pricing and related rate fences (Kimes, 1994;
Choi and Mattila, 2003; Kimes and Wirtz,
2003; Wirtz and Kimes, 2007). This study
extends prior research relating to customers’
reactions to demand-based pricing by demonstrating that the actual price paid for a given
service has a direct and negative effect on
customers’ return intentions. Furthermore,
regardless of how satisfied a customer is with
the service experience, this is not sufficient to
override the direct influence that price has over
intent to use the brand again in the future. This
finding is consistent with Keaveney (1995) who
found, that even when satisfied with a service
provider, customers may switch providers on
the basis of price. While the services literature
has tended to focus on service quality, satisfaction, service encounters and service design as
antecedents of customer loyalty, the findings of
this study, coupled with those of Keaveney
(1995), suggest that price is an additional factor
that should be considered in order to understand customer defections from service firms
fully. Findings also suggest that reward programme membership does not influence the
effect of price on return intent. While reward
programmes are designed to build barriers to
switching, this finding supports that of Mattila
(2006) regarding customers’ perceptions of low
switching costs associated with rewards programmes. It also supports the notion that
reward programmes will not induce loyalty in
the absence of an emotional bond with the
brand. It is that emotional bond, or affective
commitment, that is required to ensure repeat
patronage (Mattila, 2006).
MANAGERIAL IMPLICATIONS
Research has shown that increases in customer
retention result in increased profitability for the
service firm (Bolton, 1998; Rust et al., 1995).
This calls for management to gain an understanding of the key variables driving customer
Journal of Revenue and Pricing Management Vol. 7, 4 357–369 & 2008 Palgrave Macmillan, 1476-6930
Noone and Mount
switching so that appropriate strategies can be
developed in order to maximise customer
retention. Findings of this study indicate that
while variables such as customer satisfaction
and service quality are important drivers of
customer retention (this and previous studies
found a direct and positive effect of these
variables on return intent), price has a direct
and negative effect on return intent. The
proposition that customers may switch services
for price-related reasons implies a need for
careful management of pricing policies, especially when firms charge higher-than-competitive prices or are considering increasing rates,
service charges or penalties.
The initial reaction to this study’s findings
may be to suggest that rates be capped at some
point to minimise the number of customers lost
due to price. However, the notion of capping
rates may not sit well with revenue managers,
particularly those in excess demand markets.
Take the current Manhattan hotel market as an
example. High demand levels have elicited a
very aggressive response from hotel revenue
managers in terms of price. The spread
between the lowest and highest rates offered
at hotels in Manhattan used to be 30–40 per
cent. That spread has now increased to 300 per
cent because top-end rates have been pushed so
high (McCartney, 2007). While the Manhattan
market is not representative of all markets, it
does provide a good illustration of how
aggressively revenue managers can act in terms
of price when demand exceeds supply.
While it is appealing to focus on short-term
revenue gains in an excess demand situation
(particularly where upper management and
ownership provide pressure to maximise rates
in the short term), the potential negative effect
on long-term revenue streams of alienating
customers due to price has to be considered.
Management need to develop a comprehensive
understanding of the price sensitivity of their
different market segments. A basic tenet underlying the implementation of revenue management is that customers will segment themselves
based on their willingness to pay. However, as
illustrated by the example in the introduction
to this paper, a customer may pay a rate on a
given occasion because the need or desire to be
at a certain location at a certain time. However,
that does not mean that customer is happy to
pay the rate, and even if satisfied with the
experience, may not be willing to patronise the
brand in the future due to rate resistance.
Therefore, we suggest that management should
actively investigate the price sensitivity of their
various market segments. Armed with knowledge of the price thresholds of customer
segments, management can incorporate consideration of the strategic implications of price
increases when making short-term pricing
decisions during high demand periods.
Price sensitivity measurement (PSM) and
conjoint analysis represent two techniques that
can be applied to determine the price sensitivity of different customer segments. PSM reveals
customer price perceptions by determining the
level of customer price resistance over a range
of prices as they relate to quality perceptions.
For example, Taco Bell used PSM when it
introduced value pricing to the quick-service
restaurant industry. Rather than first developing a food item and then determining what the
price should be, Taco Bell first determined
what customers were willing to pay for a
specific type of item and then determined what
they needed to do to develop a product in that
price range (Lewis and Shoemaker, 1997). The
application of PSM has been demonstrated in
the lodging industry, with Lewis and Shoemaker (1997) applying the technique to
determine the price sensitivity of an association
meeting segment. Documentation of the
application of PSM in other hotel customer
segments and across other industries such as the
car rental and airline industries could be useful
to provide service managers with insights into
the efficiency of PSM implementation and the
information that it can yield for making pricing
decisions.
Conjoint analysis can also be used to
determine what customers are willing to pay
for a service experience. Specifically, conjoint
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Effect of price on return intentions
analysis examines how customers trade off
different price levels versus the features of a
product or service that they most desire. Based
on the outcomes of the analysis, product/
service offerings or price can be modified to
match consumer behaviour and expectations.
For example, Marriott Corporation used conjoint analysis in the design of their Courtyard
brand (Wind et al., 1989).
The notion that price directly influences
return intentions also highlights the need for
service firms to differentiate the service
experience provided, whether that is the
tangible or intangible elements of the experience (or both), from the competition in order
to avoid competing on price alone. If unique
elements can be introduced to the service
experience, customers are less able to compare
competitive offerings and may, as a result, be
less likely to use price as a key determinant of
service provider choice. For example, Wyndham International’s differentiation strategy is
centred on personalised service. When a guest
joins the Wyndham ByRequest programme, he
completes a comprehensive profile including
general and contact information, room preferences (eg room location, needed extra items),
credit card and express check-in/check-out
preferences, personal interests (eg activities,
readings, spectator sports) and preferred beverages and snacks. This information is complied
at Wyndham’s headquarters and a pledge is
made to the guest that, irrespective of which
Wyndham property he visits, he can expect the
same level of personalised service (Piccoli et al.,
2003).
Bundling (or packages) can also be used to
obscure the price of elements of a service or
product offering and make competitor comparisons more difficult (see eg, Dolan and
Simon (1996), Guiltinan (1987), Hanson and
Martin (1990), Soman and Gourville (2001),
Stremersch and Tellis (2002) for a discussion of
bundling). In fact, bundling was identified as an
important future component of successful
pricing at the 2006 Revenue Management
and Price Optimization conference (Garrow
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et al., 2006). Bundling can take a number of
forms. For example, some hotel companies
offer all-inclusive vacation packages (eg Club
Med) while others bundle one or several
amenities (eg room with breakfast; room,
breakfast and valet parking). Moreover, service
providers across industries can partner to
provide packages (eg vacation packages that
include hotel and air fare).
Furthermore, given that this study’s findings
suggest that reward programme membership
does not moderate the effect of price on return
intentions, service providers must be conscious
of rate strategies that suggest that reward
programme members are a captive market.
Reward programme members will also leave
because of rate dissatisfaction. With, for
example, the typical travel
