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Revenue management pricing in the hotel sector: Reducing perceived unfairness to encourage willingness to pay

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In a context of ever-increasing competition, revenue management pricing (RMP) has become a strategic tool for companies with limited capacity. However, despite its considerable appeal, studies show that RMP has mixed reactions from consumers. The aim of this research is to test levers of actions that can help reduce the perceived unfairness of RMP and thus promote willingness to pay (WTP). Two quantitative samples ( N 1 = 325; N 2 = 280) allowed us to validate the measurement instruments for the concepts mobilized and to test two explanatory ‘fairness-based pricing’ models. The results show that fairness and transparency have strong positive individual and interaction effects on reducing the cognitive dimensions of perceived unfairness and on reinforcing WTP. However, the effects on the affective dimensions are not confirmed in the two models tested.
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General introduction
In a market economy characterized by a logic of
competition, the performance of companies inevita-
bly requires innovation in products and in marketing
approaches. Among the marketing innovations
developed in the services sector over the last few
decades is the practice of revenue management
(RM). Originally, known as yield management, RM
(Appendix 1) has gradually been augmented by new
levers for optimizing the range of service offerings
and prices and has become a global management
strategy in companies characterized by perishable
assets subject to erratic demand (Domingo-Carrillo
et al., 2019; Weatherford and Bodily, 1992). RM is
based on accurate knowledge of consumer
Revenue management pricing in
the hotel sector: Reducing perceived
unfairness to encourage
willingness to pay
Sourou Méatchi
University of Angers, France
Sandra Camus
University of Angers, France
Abstract
In a context of ever-increasing competition, revenue management pricing (RMP) has become a strategic
tool for companies with limited capacity. However, despite its considerable appeal, studies show that
RMP has mixed reactions from consumers. The aim of this research is to test levers of actions that
can help reduce the perceived unfairness of RMP and thus promote willingness to pay (WTP). Two
quantitative samples (N1 = 325; N2 = 280) allowed us to validate the measurement instruments for the
concepts mobilized and to test two explanatory ‘fairness-based pricing’ models. The results show that
fairness and transparency have strong positive individual and interaction effects on reducing the cognitive
dimensions of perceived unfairness and on reinforcing WTP. However, the effects on the affective
dimensions are not confirmed in the two models tested.
Keywords
perceived equity, perceived transparency, perceived unfairness, pricing, revenue management, willingness
to pay, yield management
Corresponding author:
Sourou Méatchi, UFR Esthua Tourism and Culture, GRANEM (ANgevin Research Group in Economics and Management),
University of Angers, 7, allée François Mitterrand, BP 40455, 49004 ANGERS Cedex 01, Angers, France.
Email: s.meatchi@gmail.com.fr
954760RME0010.1177/2051570720954760Recherche et Applications en Marketing (English Edition)Méatchi and Camus
research-article2020
Article
2 Recherche et Applications en Marketing (English Edition) 00(0)
behaviour, very fine segmentation of demand and
real-time modulation of capacity (supply) in order to
allocate the right price to the right customer at the
right time (Abrate et al., 2019). Since 1980s, the
practice of RM has fostered the emergence of a new
pricing approach in the services sector. This new
pricing paradigm, known as pricing revenue man-
agement pricing (RMP), has been made more robust
through the development of information technology
and especially the Internet (Noone, 2016; Vives
et al., 2018). With the development of artificial intel-
ligence techniques (algorithms, machine learning,
cognitive sciences, etc.), the practice of RMP is likely
to be extended and generalized within service com-
panies (transport, hotels, restaurants, etc.). RMP ena-
bles service companies to optimize their revenues.
For the consumer, price is a decisive variable in the
process of choosing services (hotel stay, visit to a
theme park, car rental, etc.). However, prices based
on RMP are subject to mixed perceptions. Some con-
sumers consider them to be completely fair, while
others find them unacceptable. Indeed, for the same
journey and within the same time slot, air or train
fares can be very different from one customer to
another. Similarly, booking a hotel room a long time
in advance (early booking) is not always enough to
obtain advantageous prices compared to customers
who book at the last minute and who may obtain
knock-down prices. Faced with this dilemma, con-
sumers find themselves in a state of bewilderment
that often results in a negative image of RMP. For
Camus et al. (2014), regardless of the price paid by
the customer (lower or higher than the expected
price), the risks of perceived unfairness with regard
to RMP are high. In the case of a disadvantageous
price, customers may find it difficult to accept that
they could have paid less for the same service. In the
case of a favourable price, despite its positive per-
ceived value, the RM-based price may also be con-
sidered unfair because of its discriminatory nature.
Perceived unfairness is clearly a permanent risk for
companies that practice RMP. In light of the above
findings, the central question of this study is to under-
stand how perceptions of unfairness regarding RMP
are manifested and what levers might be used to
reduce these perceptions and increase consumers’
willingness to pay (WTP). Answering these ques-
tions gives rise to several theoretical and managerial
contributions. On the theoretical level, our study
responds to the call by a number of authors (e.g.
Colquitt et al., 2015; Kimes and Wirtz, 2015; Rupp
et al., 2017) for researchers to further examine the
concept of perceived unfairness because, in their
view, this particular form of injustice is particularly
salient for those who have experienced it. Our
research also aims to provide theoretical and empiri-
cal insights into the effects of fairness and transpar-
ency on the perception and acceptability of prices
arising from RMP. To this end, we elaborate and dis-
cuss a fairness-based pricing model. We first draw on
the main literature on the subject (e.g. Kahneman
et al., 1986; Sahut et al., 2016; Xia et al., 2004),
which leads us to position perceived transparency
and perceived equity (fairness) as two independent
explanatory variables in their relationship with per-
ceived unfairness and WTP (Model 1). Second, we
mobilize other approaches (e.g. Maxwell, 2008;
Noone, 2016; Zhang and Jiang, 2014) which lead us
to consider the possible moderating role of perceived
transparency on the relationship between perceived
equity and perceived unfairness, on one hand, and on
the relationship between this independent variable
and WTP, on the other hand (Model 2). Our research,
therefore, aims to test and compare two models – a
model with two independent variables and a model
with one independent variable and a moderator vari-
able – in order to determine their performance in
reducing perceived unfairness and increasing WTP
prices based on RMP. From a managerial point of
view, our research should help service firms to better
understand the phenomenon of perceived unfairness
with respect to RMP. It should also provide them with
new strategic and operational levers to reduce this
phenomenon and thus promote WTP. The article is
organized in four main sections. Section ‘Literature
review on perceptions of and WTP prices based on
RMP: A varied but limited literature’ presents the lit-
erature review and its limitations. Section ‘Comparing
the research hypotheses of the two models’ discusses
the model and research hypotheses. Section ‘Research
methodology’ describes the methodology used to col-
lect and analyse the empirical data. Section ‘Results
of the research’ presents the research findings.
Following these four sections, a general conclusion
discusses the findings and suggests possibilities for
future research.
Méatchi and Camus 3
Literature review on
perceptions of and WTP
prices based on RMP: A
varied but limited literature
This article is situated within the literature on the
perception of prices based on RMP. Price percep-
tion can be defined as a judgement made by con-
sumers regarding the monetary amount they are
required pay to acquire a product. This judgement
may be positive (perceived fairness) or negative
(perceived unfairness) and leads the consumer to
accept or refuse the transaction (Bolton et al., 2003;
Lu et al., 2019). Equitable pricing is an ever-present
issue because it is of daily concern to most consum-
ers. Indeed, whether it concerns the price of petrol,
medical expenses, or the dynamic pricing on ama-
zon.com, most acts of consumption are associated
with a price. However, despite their importance in
transaction systems, prices often pose problems of
fairness. For instance, if an Amazon customer dis-
covers that the price of the same product (a CD, a
book, a toy, etc.) varies from one moment to another
or from one context to another, he or she may
become angry with the company (Adamy, 2000;
Tripathi, 2017). This example shows how prices
and in particular RM-based prices can lead to a per-
ception of unfairness and have damaging conse-
quences for firms. The literature also postulates that
perceived unfairness is the main cause of reduced
WTP prices resulting from RMP (Noone and
Mattila, 2009; Wu et al., 2012). Yet, despite the
richness of the existing literature, there are few
empirical studies on how perceptions of and the
acceptability of RMP could be improved. It is there-
fore important to explore new avenues of research
on the strategies to be implemented in order to limit
the risks of perceived unfairness and its corollaries
in the context of RMP.
Theoretical and conceptual
framework of the research
As noted above, despite the abundant literature on
the subject, few empirical models have been tested
on strategies to reduce the perceived unfairness of
RMP and the WTP prices associated with it. The
purpose of this study is to help fill this gap
by proposing and comparing two fairness-based
pricing models. Both are based on the theory of fair
pricing. Formulated by Xia et al. (2004) in accord-
ance with the work on the dual entitlement principle
(Kahneman et al., 1986) and on theories of social
(Adams, 1965) and organizational (Greenberg,
1987) justice, fair price theory analyses the way in
which consumers judge prices and the treatment
they receive in transactional relationships. This psy-
cho-economic theory emphasizes two fairness fac-
tors: perceived equity, on one hand, and perceived
transparency, on the other hand. According to Xia
et al. (2004), both factors are important to consum-
ers because they are in their best interests. If con-
sumers feel that their contribution to a transaction is
not being rewarded fairly, they may feel they have
suffered an injustice. Similarly, consumers may feel
that it is unfair if the information made available is
not transparent (Campbell, 2007). The literature
also postulates that in the context of RMP, the lack
of perceived equity and transparency generally
leads to a decline in WTP (Kimes and Wirtz, 2016;
Noone and Mattila, 2009).
Before analysing the cause-and-effect relation-
ships underlying our two research models, we need
to first present the various concepts mobilized
through the literature review and, in particular,
through analysis of the theory of fair pricing.
Perceived price equity (PPE). In the context of prices,
the principle of fairness (Deutsch, 1975; Xia et al.,
2004) considers that exchange relations are fair
when the cost–benefit ratio is balanced. This princi-
ple also postulates that fairness entails giving all
consumers the same chances of access to a product
or a price. Deutsch’s (1975) model suggests that in
the context of transactional exchanges, the principle
of equity (the cost–benefit ratio) must be taken into
account. This distributive justice approach has been
adopted in numerous research studies on prices (e.g.
Inman and Nikolova, 2017; Taylor and Kimes,
2011). In this study, we use the concept of PPE as
understood not only by Deutsch (1975) but also by
Oliver and Swan (1989a, 1989b), Xia et al. (2004)
and Vukadin et al. (2019)
Perceived transparency of information (PTI). In addi-
tion to PPE, PTI also plays an important role in
4 Recherche et Applications en Marketing (English Edition) 00(0)
judging prices (Noone, 2016; Sahut et al., 2016).
According to Heyman and Mellers (2008), as part
of the purchasing process, consumers assess not
only the price level but also the transparency of
information on the price fairness ratio, the condi-
tions of sale and the benefits associated with each
price level. In doing so, they generally rely on infor-
mation made available to them by the company and,
where appropriate, by other stakeholders (other cus-
tomers, consumer associations, public administra-
tions, etc.). If the information available does not
allow consumers to understand the company’s pric-
ing policy, they may perceive it as unfair. Transpar-
ency of information depends on the clarity, accuracy,
consistency and reliability of the information pro-
vided (Colquitt et al., 2015). Many authors (e.g.
Choi and Mattila, 2005; Ferguson et al., 2014) show
that the absence or inadequacy of price information
can lead consumers to doubt the fairness of the
price. However, providing justifications for pricing
policy would reduce negative judgements and
favour WTP (Bearden et al., 2003; Li et al., 2019).
Perceived unfairness of RMP. In the context of RMP,
perceived unfairness is generally defined as a nega-
tive perception of the value of a transaction (Camus
et al., 2014). In the hospitality sector, studies have
shown that a customer who pays more than some-
one else for a similar service where there is no dis-
cernible difference in quality may view the situation
as unfair (Kimes, 1994). For Xia et al. (2004), price
unfairness has two dimensions: one is cognitive, the
other one is affective. The cognitive dimension
indicates that perceptions of unfairness are based on
a comparison with a relevant standard (e.g. average
market price), a benchmark (e.g. the price of a pre-
vious purchase) or a norm (e.g. membership rate).
The affective dimension, however, concerns into
negative emotions that accompany cognition. Both
dimensions will be used in this research.
WTP RMP prices. In consumer behaviour research,
WTP is generally defined as the likely attitude that
a consumer may take towards a price (Dodds et al.,
1991; Tanford et al., 2018). According to Le Gall-
Ely (2009), WTP is a part of the price perception
process and is similar to the concepts of benchmark
price and acceptable price. It is also related to other
variables influencing the decision process (satisfac-
tion, loyalty, etc.). In perceptual approaches, WTP
is used to measure either the acceptability of a spe-
cific price for a given product (e.g. WTP €2 for a
small bottle of water in a railway station; WTP €60
or €150 for a Paris–Nice flight), or the acceptability
of a family of prices (e.g. WTP dynamic airline
prices). In this study, we will be concerned with the
WTP regarding a family of prices or a pricing
model. The reason for this preference is that our
study is oriented towards measuring the acceptabil-
ity of a pricing model (in this case, RMP) and not
towards measuring the acceptability of a specific
amount (for example, WTP €950 for a smartphone).
Consequently, measurement by qualitative or
semantic items will be used. This approach has
already been used by other consumer behaviour
researchers. For example, in her study on WTP for
airline tickets, Maxwell (2002) measured WTP with
semantic indicators (Appendix 2). In the hotel sec-
tor, Noone and Mattila (2009) adapted the semantic
scale of Grewal et al. (1998) to measure WTP vari-
able hotel room prices.
Comparing the research
hypotheses of the two models
Drawing on the literature, we put forward two fair-
ness-based pricing models. According to the theory
of fair pricing (Xia et al., 2004), perceived equity
and perceived transparency have positive effects on
price perception. However, no empirical models
have yet been tested regarding the effects of per-
ceived equity and perceived transparency on reduc-
ing perceived unfairness and on WTP in the context
of RMP as practised by hotels. Moreover, no
research to our knowledge has yet investigated the
effects of interactions between perceived equity and
perceived transparency in the context of RMP. Yet,
the literature review suggests that the effect of equi-
table pricing on perceived unfairness depends on the
information transparency policy (Maxwell, 2008). It
thus appears that the perceived equity of pricing and
the PTI could have, on one hand, individual and
direct effects (model 1) and, on the other hand, inter-
action effects with perceived equity as an independ-
ent variable and perceived transparency as a
moderator variable (model 2). We will test and
Méatchi and Camus 5
compare the two models in order to determine which
one works best in reducing perceived unfairness and
in strengthening WTP. With this in mind, we first
present hypotheses on the individual and direct
effects of perceived equity and perceived transpar-
ency on the reduction of perceived unfairness and on
WTP (model 1). In a second step, hypotheses on the
effects of interactions between perceived equity
(independent variable) and perceived transparency
(moderator variable) will be formulated (model 2).
Individual effects of perceived equity
and transparency on perceived
unfairness and WTP (Model 1 –
Figure 1)
According to heuristic approaches to social justice
(e.g. Brown-Liburd et al., 2018; Lind, 2001), in sit-
uations of uncertainty, individuals make decisions
either by limiting themselves to the first solution
identified or by proceeding through sequential steps
that enable them to progressively eliminate unfa-
vourable alternatives and retain only a limited range
of solutions perceived as optimal. Consumers’ heu-
ristic behaviours can therefore lead them to take
shortcuts in their judgements and limit themselves
to the first considerations they identify (e.g. the
cost–benefit ratio, available information, proce-
dures, etc.). Under these conditions, consumers
would not need fairness and transparency simulta-
neously in order to assess the fairness or unfairness
of a price. The reduction of perceived unfairness
and WTP could therefore occur as a result of a sin-
gle main factor. This primary factor may be either
the perceived equity of the price or the PTI.
Customers for whom the most important criterion is
fairness will be satisfied with the balance of the
cost–benefit ratio in assessing the equity of a price,
while those who are more concerned with transpar-
ency will focus their attention on the quantity and
quality of information available to them (Miao and
Mattila, 2007). In what follows, we present and test
the hypotheses that PPE and PTI each have positive
individual effects on reducing perceived unfairness
and on WTP in the context of RMP.
Effects of PPE on the reduction of perceived unfairness
and on WTP. Much previous research postulates
that lack of equity is a factor in perceptions of
unfairness in RMP. According to Kimes (1994) and
Kimes and Wirtz (2016), the application of the dual
entitlement principle (Kahneman et al., 1986) in the
context of prices suggests that RMP is unfair. This
is because prices based on RMP are not always
linked to production costs but to the exploitation of
economic anomalies in the market. Campbell
(2007) argues that consumers feel that prices are
unfair when they have no reasonable justification.
However, when consumers find it in their interest to
have a pricing policy, they become less demanding
in terms of price justice (Camus et al., 2014; Kimes
and Wirtz, 2002). It can be seen from the literature
that some authors (e.g. Bolton et al., 2003) focus
mainly on analysing the role of fairness in price per-
ception and WTP. In the light of the factors just
mentioned, it would seem that, all other things
being equal, fair pricing may be sufficient to reduce
perceived unfairness and promote WTP. Our first
three research hypotheses stem from this premise.
H1. Perceived equity has a positive effect on
reducing the cognitive dimension of perceived
unfairness with respect to RMP
H2. Perceived equity has a positive effect on
reducing the affective dimension of perceived
unfairness with respect to RMP
H3. Perceived equity has a positive effect on
willingness to pay the prices resulting from RMP
Effects of PTI on the reduction of perceived unfairness
and on WTP. Regarding the individual effects of
perceived transparency, Miao and Mattila (2007)
postulate that the quality of the information availa-
ble plays a fundamental role in price perception. In
turn, Morwitz et al. (1998) suggest that the way in
which prices are presented (complex vs simple dis-
play) is an antecedent of perceived transparency,
which is itself a factor in perceived equity and WTP.
It has also been shown that consumers’ heuristic
behaviour often leads them to make rapid judge-
ments by limiting themselves to the basic criteria
available to them (Lind, 1992, 2001). Consumers
for whom the most important criterion is transpar-
ency will use only this one indicator in assessing the
fairness of a price. They may focus on the clarity,
6 Recherche et Applications en Marketing (English Edition) 00(0)
consistency and reliability of information in order
to determine whether the price is fair (Maxwell,
2008; Tanford et al., 2012). Under these conditions,
when individuals do not have transparent informa-
tion that allows them to assess their benefits in rela-
tion to their costs (internal fairness) or to assess the
cost–benefit ratio of other customers (external fair-
ness), they may consider that the price paid or
observed is inequitable. To mitigate the sense of
perceived unfairness and its consequences on WTP,
some authors (Campbell, 2007; Li et al., 2019) sug-
gest using transparency of information, since this
variable may play an important individual role in
price perception. Drawing on the literature on price
transparency, we put forward the following
hypotheses.
H4. Perceived transparency has a positive effect
on reducing the cognitive dimension of perceived
unfairness with respect to RMP.
H5. Perceived transparency has a positive effect
on reducing the affective dimension of perceived
unfairness with respect to RMP.
H6. Perceived transparency has a positive effect
on willingness to pay the prices resulting from RMP.
Interaction effects of perceived
equity and perceived transparency
on perceived unfairness and WTP
(Model 2 – Figure 2)
As we have already seen through the literature
review, in models of price perception, the effects of
perceived equity and perceived transparency are
generally studied separately or sequentially.
However, no model to our knowledge has empiri-
cally tested the effects of interactions between per-
ceived equity and perceived transparency on the
reduction of perceived unfairness and on WTP.
However, some studies (e.g. Maxwell, 2008; Sahut
et al., 2016) suggest that in order to reduce per-
ceived unfairness in RMP and promote WTP, any
fairness-based approach needs to be accompanied
by a policy of information transparency. According
to Maxwell (2008), a fairness policy that is not
accompanied by transparent information is ineffec-
tive in mitigating perceptions of injustice and
enhancing WTP. In the context of RMP, perceived
equity and perceived transparency would therefore
produce positive interaction effects in terms of
reducing perceived unfairness and in terms of WTP.
Based on the above, we assume that there are inter-
action effects between the perceived equity of the
price and the PTI on the reduction of perceived
unfairness and on WTP. This assumption leads us to
put forward the following hypotheses.
H7. Perceived equity and perceived transpar-
ency interact positively to reduce the cognitive
dimension of perceived unfairness with respect to
RMP.
H8. Perceived equity and perceived transpar-
ency have positive interaction effects on reducing
the affective dimension of perceived unfairness with
respect to RMP.
H9. Perceived equity and perceived transpar-
ency have positive interaction effects on willingness
to pay the prices resulting from RMP.
In this second model (Figure 2), perceived equity
retains its status as an independent variable, while
perceived transparency becomes a moderator varia-
ble. This new distribution of roles between the two
variables is based on distributive justice (Oliver and
Swan, 1989a; Xia and Monroe, 2010) and heuristic
approaches to price equity (Brown-Liburd et al.,
2018; Lind, 2001; Maxwell, 2008). These different
approaches have shown that in the context of prices,
customers tend to consider fairness criteria first.
According to Maxwell (2008), the primary factor that
consumers evaluate in the context of prices is their
fairness. If the price observed or obtained is different
from the usual price or the price paid by other custom-
ers, the consumer then looks for reasons justifying the
observed price differences. Under these conditions,
transparency of price information becomes a modera-
tor of the effects of perceived equity on perceived
unfairness and on WTP.
Research methodology
In this section, we present the methodology for data
collection and analysis and the procedure for select-
ing and validating measurement instruments.
Méatchi and Camus 7
Collection and pre-analysis of
quantitative data
In order to operationalize the constructs and test
the conceptual model, we conducted two quantita-
tive data collections. The first (N1 = 325) was car-
ried out by means of a questionnaire administered
face-to-face. The sample is very much varied in
terms of age (21–25 years: 42%; 26–35 years:
15%; 36–45 years: 20%; 46 years and above:
23%), gender (women: 62%; men: 37%; others:
1%) and socio-professional category (PCS+:
23%; PCS−: 29%; retired: 4%, student/doctoral
students: 24%; others: 20%). This first collection
allowed us to pre-test the measurement scales of
the variables mobilized. The second collection
(N2 = 280) was carried out using a scenario-based
experimental method (Bolton et al., 2003;
Lavorata et al., 2005). A 2 × 2 factorial design
(Appendix 3) used for this purpose. The experi-
mental scenarios were constructed with the help
of three hoteliers from the city of Angers (Hôtel
d’Anjou 4*, Hôtel Les Trois Lieux 3* and Hôtel
Iéna 2*). Respondents were randomly assigned to
the four experimental conditions, with each sub-
ject assigned to a single experimental group. It is
therefore an inter-subject experiment. Data col-
lection was carried out through the Internet using
an access panel of the research company
CReATESTS. In this way, a total sample of 280
respondents was interviewed. The socio-demo-
graphic characteristics of the sample are relatively
varied in terms of gender (women: 41%; men:
59%), age (21–30 years: 25%; 31–40 years: 25%;
41–50 years: 25%; 51 years and above: 25%) and
socio-professional category (PCS+: 23%; PCS−:
30%; intermediate occupations: 18%; retired: 4%;
other: 25%).
Validation of measurement
instruments
The measurement instruments used were taken
from the existing literature. They were all sub-
jected to purification tests and statistical analyses
in accordance with Churchill’s (1979) paradigm,
Rossiter’s (2002, 2011) recommendations and
Fornell and Larcker’s (1981) criteria. Statistical
tests confirmed the reliability and validity of the
concepts used (Appendix 4).
Measurement of perceived unfairness
with respect to RMP
The perceived unfairness scale was taken from
Méatchi and Camus (2018b). This scale comprises
three dimensions (perceived normative deviance,
perceived opacity and negative affects) and nine
reflective items (Jarvis et al., 2003) with an
explained variance of 78.52%. The high correlation
between normative deviance and perceived opacity
led us to test a second-order model with two dimen-
sions, namely, a cognitive dimension with five
items (α: 0.89; p: 0.92; AVE (Average Variance
Extracted): 0. 70) and an affective dimension with
three items (α: 0.74; p: 0.85; AVE: 0.66). Cronbach’s
alpha (α) and Dillon–Goldstein’s rho (p) are satis-
factory in that they all have coefficients greater than
0.07, the threshold usually recommended in the
psychometric literature. Finally, the scale was inte-
grated into the explanatory model, thus enabling us
to test its predictive validity.
Measurement of the other constructs
The scales of the other constructs (WTP, perceived
equity and perceived transparency) were also taken
from the literature and then tested for reliability
and validity. For WTP, we used and adapted the
Dodds et al.’s (1991) five-item scale. From the
five indicators, we selected the three most
appropriate for our research objectives.
Reliability and validity tests were very satisfac-
tory (α = 0.74; rho = 0.85; AVE = 0.65). For
measurement of perceived equity, we used three
items from the Oliver and Swan’s (1989) scale.
The results of the statistical tests are also satisfac-
tory (α = 0.81; rho = 0.88; AVE = 0.71). Finally, in
order to measure perceived transparency, indica-
tors of informational justice (Colquitt et al., 2015)
were chosen. Three indicators for measuring infor-
mational transparency (clarity, explanation and
precision) were selected and tested. The results of
the reliability and validity tests are likewise satis-
factory (α = 0.65; rho = 0.81; AVE = 0.57).
8 Recherche et Applications en Marketing (English Edition) 00(0)
Justification of the choice of structural equations
for testing the explanatory model. Although the
data from experimental designs are traditionally
analysed using variance analysis (ANOVA), we
decided to use the structural equation method
(SEM) to process our data. The SEM has a num-
ber of advantages. First of all, it is very efficient
for processing any type of data as long as the
variables are measured with numerical scales
(Baron and Kenny, 1986: 1177). Second, unlike
ANOVA, structural equations can handle all the
relationships between variables in a model simul-
taneously. Finally, Iacobucci (2008) showed that
structural equations are a superior method of
ANOVA and regressions. These various reasons
justify our choice of the SEM for testing the
model.
Results of the research
The first fairness-based pricing model (Figure 1)
tested the individual effects of each of the inde-
pendent variables (perceived equity and perceived
transparency) on reducing perceived unfairness and
on WTP. The second model (Figure 2) tested the
interaction effects between an independent variable
(perceived equity) and a moderator variable
(perceived transparency). Summary tables of the
scores of the estimated parameters (Addinsoft,
2019) are provided in Appendices 5 and 6. The
results of the different tests are commented below.
Individual effects of perceived equity
and perceived transparency on the
reduction of perceived unfairness and
on WTP
In order to determine whether PPE and PTI indi-
vidually affect the reduction in perceived unfairness
and WTP, we analysed the individual effects of each
of these two variables. The results are presented in
the following paragraphs.
Figure 3 shows that under the individual
effects of PPE and PTI, the cognitive (R2: 0.68)
and affective (R2: 0.16) dimensions of perceived
unfairness varied by 0.68% and 0.16%, respec-
tively. With regard to WTP (R2: 0.71), the varia-
tion was 0.71%. We now need to analyse the
direction of the relationships and the scores in
each relationship to confirm the hypotheses of the
first model tested.
Effects of PPE. Recall that the first condition of our
experimental design is to measure the effects of
Figure 1. Individual effects of perceived equity and transparency on perceived unfairness and WTP (Model 1).
Méatchi and Camus 9
Figure 2. Moderating role of perceived transparency on the relationship between perceived equity and perceived
unfairness and WTP (Model 2).
Figure 3. Model 1 with the statistical scores of the effects tested.
perceived equity on perceived unfairness and on
WTP. The parameter scores for this experimental
condition are as follows.
Table 1 shows that PPE has positive and sig-
nificant effects on reducing the cognitive dimen-
sion of unfairness (β: 0.76; p < 0.01; f2: 1.70) and
10 Recherche et Applications en Marketing (English Edition) 00(0)
Effects of PTI. Under the second experimental con-
dition, we tested the individual effects of perceived
transparency on perceived unfairness and WTP. The
aim was to find out whether, on an individual basis,
perceived transparency on reduced perceptions of
unfairness and increased WTP. The statistical scores
obtained are shown in Table 2.
The above scores show that perceived trans-
parency (PTI) has positive and significant
Table 2. Scores of effects of perceived transparency of information (PTI).
Endogenous variables Exogenous variables βSE t Pr > |t|f2
Perceived
transparency of
information (PTI)
CDU 0.20 0.03 5.66 0.00*** 0.12
ADU 0.23 0.06 4.14 0.00*** 0.06
WTP 0.12 0.03 3.58 0.00*** 0.05
β: regression; SE: standard error; t: T test; Pr > |t|: threshold of significance; f2: effect size; CDU: cognitive dimension of perceived
unfairness; ADU: affective dimension of perceived unfairness; WTP: willingness to pay.
***p < 0.01.
Table 1. Scores of effects of perceived price equity (PPE).
Endogenous variables Exogenous variables βSE t Pr > |t|f2
Perceived price
equity (PPE)
CDU 0.76 0.03 21.70 0.00*** 1.70
ADU −0.38 0.06 −6.68 0.00*** 0.16
WTP 0.81 0.03 24.72 0.00*** 2.21
β: regression; SE: standard error; t: T test; Pr > |t|: threshold of significance; f2: effect size; CDU: cognitive dimension of perceived
unfairness; ADU: affective dimension of perceived unfairness; WTP: willingness to pay.
***p < 0.01.
Hypotheses Confirmed
H1. Perceived equity has a positive effect on reducing the cognitive dimension of perceived
unfairness with respect to RMP
Yes***
H2. Perceived equity has a positive effect on reducing the affective dimension of perceived
unfairness with respect to RMP
No
H3. Perceived equity has a positive effect on willingness to pay the prices resulting from RMP Yes***
RMP: revenue management pricing.
***Hypothesis confirmed at the 1% threshold (p < 0.01).
individual effects on reducing the cognitive (β:
0.20; p < 0.01) and affective (β: 0.23; p < 0.01)
dimensions of perceived unfairness. The statis-
tics also show that the effects of perceived trans-
parency on WTP are positive and significant (β:
0.12; p > 0.01). These statistics confirm all the
hypotheses (H4, H5 and H6) on the individual
effects of the PTI, with a very significant thresh-
old of 0.01.
on WTP (β: 0.81; p < 0.01; f2: 2.22). However, the
effects on the reduction of the affective dimension
are negative (β: −0.38; p < 0.01; f2: 0.16). On the
basis of these statistical elements, hypotheses H1
and H3 are confirmed and hypothesis H2 is
disconfirmed.
Méatchi and Camus 11
Interaction effects of perceived equity
and perceived transparency on the
reduction of perceived unfairness and
on WTP
After testing the hypotheses regarding individual
effects, we investigated whether PPE and PTI had
positive and significant interaction effects on
reducing perceived unfairness and on WTP.
Remember that in our interaction hypotheses
(Model 2), perceived equity is the independent
variable and perceived transparency is used as a
moderator variable. Three interaction effects were
tested using partial least squares (PLS) regressions
and then the Chow test.
Testing interactions by the PLS method. The results of
testing interactions by the PLS method are shown in
Figure 4 and Table 3.
Figure 4 shows that the interaction between per-
ceived equity (PPE) and perceived transparency
(PTI) has effects on the cognitive (R2: 0.69) and
affective (R2: 0.20) dimensions of perceived unfair-
ness with respect to RMP. This interaction also
Figure 4. Model 2 with interaction effect scores.
Hypotheses Confirmed
H4. Perceived transparency has a positive effect on reducing the cognitive dimension of perceived
unfairness with respect to RMP
Yes***
H5. Perceived transparency has a positive effect on reducing the affective dimension of perceived
unfairness with respect to RMP
Yes***
H6. Perceived transparency has a positive effect on willingness to pay the prices resulting from RMP Yes***
RMP: revenue management pricing.
***Hypothesis confirmed at the 1% threshold (p < 0.01).
12 Recherche et Applications en Marketing (English Edition) 00(0)
affects WTP (R2: 0.70). The direction of the rela-
tionships and the statistical scores below will enable
the hypotheses on the interaction effects of the
model to be confirmed or not.
Comparison of Models 1 and 2 with
the Chow test
The regression coefficients shown above reveal
differences between the effects of perceived equity
in Model 1 (model without interactions and with
transparency) and the effects of the same inde-
pendent variable in Model 2 (interaction model)
(Table 4).
In order to determine whether the observed dif-
ferences (Table 5) are significant, a Chow test with
multi-group analyses (Gavard-Perret et al., 2012:
323) was carried out. The results are as follows.
The Chow test (Table 5) shows positive and sig-
nificant differences between the model without
interactions (Model 1) and the model with interac-
tions (Model 2) in the cognitive dimension of per-
ceived unfairness (β: 0.23; p < 0.01) and in WTP
(β: 0.97; p < 0.01). However, the difference is not
Table 3. Interaction effects of perceived equity (PPE) and perceived transparency (PTI).
Interaction effects Exogenous variables βSE tPr > |t|f2
PPE × PTI CDU 0.83 0.03 24.66 0.00*** 2.19
ADU −0.45 0.05 −8.30 0.00*** 0.25
WTP 0.84 0.03 25.73 0.00*** 2.38
β: regression; SE: standard error; t: T test; Pr > |t|: threshold of significance; f2: effect size; CDU: cognitive dimension of perceived
unfairness; ADU: affective dimension of perceived unfairness; WTP: willingness to pay.
***p < 0.01.
Table 4. Comparison between Model 1 and Model 2.
Exogenous variables
Model 1
Effects of perceived equity without
moderation of perceived transparency
Model 2
Effects of perceived equity with moderation
of perceived transparency
CDU 0.76 0.83
ADU −0.38 −0.45
WTP 0.81 0.84
CDU: cognitive dimension of perceived unfairness; ADU: affective dimension of perceived unfairness; WTP: willingness to pay.
Table 5. Results of the Chow test.
Exogenous variables
β
(difference)
t
(observed)
t
(critical) DoF p-value Significant
CDU 0.23 2.29 1.96 558 0.02** Yes
ADU 0.25 1.33 1.96 558 0.18 No
WTP 0.97 4.35 1.96 558 0.01** Yes
CDU: cognitive dimension of perceived unfairness; ADU: affective dimension of perceived unfairness; WTP: willingness to pay; DoF:
degree of freedom.
**p < 0.05.
Méatchi and Camus 13
Hypotheses Confirmed
H7. Perceived equity and perceived transparency interact positively to reduce the cognitive dimension of
perceived unfairness with respect to RMP
Yes**
H8. Perceived equity and perceived transparency have positive interaction effects on reducing the affective
dimension of perceived unfairness with respect to RMP
No
H9. Perceived equity and perceived transparency have positive interaction effects on willingness to pay the
prices resulting from RMP
Yes**
RMP: revenue management pricing.
**Hypothesis confirmed at the 5% threshold (p < 0.05).
significant with regard to the affective dimension of
perceived unfairness (β: 0.25; p < 0.18). The Chow
test scores confirm hypotheses H7 and H9 and dis-
confirm hypothesis H8.
Conclusion: Contributions,
limitations and future
research
This article has presented the findings of research
on the perception of and WTP prices based on RMP.
The study makes multiple contributions at both the
theoretical and the managerial levels.
Theoretical contributions
On the theoretical level, four main contributions
have emerged from this research. The first concerns
the empirical validation of two models for the
reduction of perceived unfairness and developing
WTP prices resulting from RMP. As previously
mentioned, despite the abundant literature, few
empirical models on strategies to reduce perceived
unfairness and on WTP have been tested in the con-
text of RMP. Second, the literature is completely
silent on the effects of interactions between per-
ceived equity and perceived transparency in the
context of RMP. Existing models are generally
exploratory, and the assumptions regarding levers
for reducing perceived unfairness and enhancing
WTP have received little empirical testing. Our
research has helped to fill this gap in the literature
by validating two fairness-based pricing models.
The first suggests that perceptual variables, particu-
larly perceived equity and perceived transparency,
have direct positive individual effects on reducing
perceived unfairness and WTP in the context of
RMP. Specifically, the confirmation of hypotheses
H1 and H3 shows that PPE has direct positive indi-
vidual effects on reducing the cognitive dimension
of perceived unfairness with respect to RMP and on
WTP. These findings reinforce the theories of per-
ceived equity (Oliver and Swan, 1989; Xia and
Monroe, 2010) and dual entitlement (Kahneman
et al., 1986) which postulate that fairness in a pric-
ing policy helps to attenuate the cognitive dimen-
sion of perceived unfairness. Conversely, the
disconfirmation of H2 suggests that perceived
equity in pricing does not have a significant effect
on the affective dimension of perceived unfairness.
The disconfirmation of this hypothesis makes it
clear that the presence of equity is not always suf-
ficient to reduce the negative effects that a con-
sumer may experience in the context of RMP. This
finding supports models postulating that, regardless
of the price paid by the customer (whether lower or
higher than the expected price), the risk of per-
ceived unfairness in RMP may still exist (Camus
et al., 2014). Indeed, in the case of an advantageous
price, despite perceived equity, RM-based pricing
may induce negative emotions (anger, disgust, guilt,
etc.) because of the relatively opaque and discrimi-
natory nature of RMP (Granados et al., 2018). With
regard to the effects of perceived transparency, the
confirmation of all the hypotheses (H4, H5 and H6)
about the individual effects of this factor shows the
critical importance of information in the context of
RMP. These findings show that consumers need to
know why in certain sectors they pay different
prices for the same product category (e.g. a train
ticket on the same route and time slot). If consumers
have clear and reliable information on the reasons
14 Recherche et Applications en Marketing (English Edition) 00(0)
for price differences, they will be more likely to
accept RMP and pay the prices resulting from this
practice.
The second theoretical contribution concerns the
comparison of the performances of the two models
tested: one with two independent variables (perceived
equity and perceived transparency), the other with an
independent variable (perceived equity) and a mod-
erator variable (perceived transparency). The Chow
test showed that the interaction between perceived
equity and perceived transparency has significant
effects in terms of reducing the cognitive dimension
of perceived unfairness and in terms of WTP. The
confirmation of hypotheses H7 and H9 shows that in
order to reduce perceived unfairness and promote
WTP, it is necessary to simultaneously mobilize
levers of equity (e.g. price as a function of room size)
and transparency (clear and reliable information,
etc.). However, the disconfirmation of hypothesis H8
reveals that the use of transparency (as a moderator) is
not always sufficient to reduce negative affect regard-
ing RMP. Other variables (e.g. the company’s compli-
ance with ethics, corporate social responsibility, etc.)
would also be among the criteria taken into account
by consumers to assess price equity. We conclude
that, therefore, the two models tested are roughly
equivalent in terms of performance in reducing per-
ceived unfairness and in strengthening WTP. What
the models have in common is that they both discon-
firm the hypotheses regarding the affective dimension
of perceived unfairness, except for the individual
effect of perceived transparency. However, they both
corroborate all the hypotheses about reducing the
cognitive dimension of unfairness and enhancing
WTP. Furthermore, comparing the performance of
perceived equity with that of perceived transparency
shows that perceived equity has positive effects on the
cognitive dimension and on WTP, but not on the
affective dimension, in either the first or the second
model. The effects of perceived transparency, how-
ever, are all positive in both models, except on the
reduction in the affective dimension in the second
model. These findings allow us to draw a second con-
clusion that perceived transparency (whether as an
independent variable or as a moderator variable)
appears to be a fundamental factor in reducing the
cognitive and affective dimensions of perceived
unfairness and in strengthening WTP. Perceived
equity, however, is highly effective in reducing the
cognitive dimension of perceived unfairness and in
promoting WTP. But it is insufficient to reduce the
affective dimension of perceived unfairness. Our
research has therefore highlighted the limitations of
pricing strategies focussed only on the benefit–cost
ratio (equity) and has shown the importance of per-
ceived transparency. These conclusions support theo-
ries according to which the affective dimension of
perceived unfairness is generally difficult to reduce
when RMP strategies are limited to improving equity
(benefit–cost ratio) without taking other factors into
account. Apart from equity and transparency, other
variables would also be important to the consumer in
the context of RMP. These include, for example, fac-
tors relating to the company’s compliance with social
norms (Maxwell, 2008; Méatchi and Camus, 2018),
ethics (Goldman and Cropanzano, 2015; Pez et al.,
2017) and corporate social responsibility (Koschate-
Fischer et al., 2016; Thiery, 2005). Integrating these
variables into an RMP strategy may be a better way to
reduce the affective dimensions of perceived unfair-
ness and to augment WTP.
The third theoretical contribution concerns fair
pricing in relation to justice and equity theory (Xia
et al., 2004) as the main analytical framework in our
research. This is an important contribution because
little previous research has adopted this theoretical
framework. Most existing models have used either
the mutual interest or dual entitlement principle
(Kahneman et al., 1986) or organizational justice
theories (Greenberg, 1987) as the basis for analys-
ing the perception of prices. However, these theo-
ries are only partial and do not provide an integrative
understanding of the issues related to justice and
WTP prices resulting from RMP (Xia et al., 2004).
By mobilizing the theory of fairness in pricing, our
research provides a broader view of strategies for
reducing perceived unfairness and strengthening
WTP. The theory of fairness-based pricing has
made it possible not only to simultaneously take
into account the cognitive and affective dimensions
of perceived unfairness but also to mobilize fairness
and transparency in the same explanatory model.
Méatchi and Camus 15
This integrative approach is used very little in mod-
els based on theories of organizational justice
(Greenberg, 1987) or on the dual entitlement princi-
ple (Kahneman et al., 1986), which are focused on
cognitive variables rather than affective variables.
The fourth and final theoretical contribution con-
cerns conceptual clarification, two-dimensional
measurement and predictive validation of the con-
cept of perceived unfairness with respect to RMP.
We mobilized this concept after defining and meas-
uring it in two dimensions (cognitive and affective).
We then tested its predictive validity by incorporat-
ing it into our explanatory model. These different
psychometric valences allow us to give perceived
unfairness a clear theoretical status differentiating it
from similar or antonymic concepts such as per-
ceived equity, something that had not yet been done
in the literature on price perception, in general, and
in models on the perception of RMP, in particular.
Managerial contributions
On the managerial level, our study also has a number
of implications. Hotel companies are generally torn
between the benefits of revenue management and the
risks of perceived unfairness associated with this
practice. While the benefits of RMP are well estab-
lished, the concern of those in the hotel industry (par-
ticularly small and medium-sized hotels) is how to
apply pricing through revenue management (RMP),
while limiting the risks of a ‘boomerang effect’. Our
research has attempted to address this issue by pro-
posing an RMP model based on fair pricing and PTI.
We refer to this model as ‘fairness-based pricing’.
Rather than being a revolutionary model, it is an
incremental approach that invites professionals to
take into consideration perceptual variables (per-
ceived equity, perceived transparency, etc.) in their
revenue management practices. From this perspec-
tive and in order to meet consumers’ expectations in
terms of equity and transparency, the hypotheses
tested and confirmed in this research suggest that
managers should complement traditional models
based on sales histories and stochastic approaches
(Belobaba, 1989; Koch et al., 2017) by integrating
equity and transparency levers. The integration of
fairness into RPM models can be achieved through
supply-side value enhancement techniques (Rivière
and Bourliataux-Lajoinie, 2017; Xia and Monroe,
2010). In other words, to implement a fairness-based
pricing policy, the company should enrich the value
of its offering when it wants to post higher prices.
Conversely, if it feels the need to post lower prices in
order to stimulate demand, it will need to review cer-
tain attributes of the offering so that customers who
have already paid the highest prices do not feel they
have been short-changed. Customers expect the price
difference to be justified by a difference in the value
of the offering and not only by the reservation date
(calendar model) or by demand pressure (threshold
curve model). Similarly, a differentiation strategy
based on hedonic and sensory attributes (e.g. the
view offered by the room, the quality of room deco-
ration, etc.) or instrumental attributes (Wi-Fi access,
minibar, etc.) can be used as an ingredient of fair
pricing. Price management based on fairness and
value for money can meet both internal and external
fairness principles (Maxwell, 2008). However, a fair-
ness policy is of little use if the company is not trans-
parent about its pricing policy. Providing customers
with clear and accurate information on the pricing
policy is essential for reducing negative cognitive
and affective reactions to RMP. Previous research
(e.g. Ayadi et al., 2017) has shown that clarity, accu-
racy, consistency and reliability of pricing informa-
tion are key criteria that enable consumers to make
their decision during the purchasing process.
Transparency of information is one of the indicators
mostly used by consumers to assess (procedural and
distributive) fairness in the context of prices. The
hypotheses corroborated in this research chime with
the postulates proposed in previous studies and show
that the provision of transparent information is one of
the key levers for reducing perceptions of unfairness
and promoting WTP. Service companies, such as the
French national railway company (SNCF), have
become aware of the challenges of transparent price
information. Since 2017, SNCF has been implement-
ing a transparency policy called the ‘Information
First’ programme. The programme was initiated in
response to the very strong dissatisfaction expressed
by customers about the information provided by the
16 Recherche et Applications en Marketing (English Edition) 00(0)
company. The real change behind this programme is
the priority given to customer information.
Limitations of the research
Regarding the limitations of our study, we are aware
that there are certain weaknesses that need to be
addressed before considering new avenues of research.
First, the global model of fairness-based pricing that we
tested focused on two fairness variables, namely, per-
ceived equity and perceived transparency. Other dimen-
sions of fairness (e.g. perceived ethics, perceived value
of the offering, etc.) were not taken into account in the
model. The absence of these variables may be the rea-
son for the disconfirmation of hypothesis H2 in the first
model and hypothesis H8 in the second model. Despite
the presence of perceived equity and transparency, con-
sumers may feel it unjust if they believe that the firm
does not respect ethical principles (Ayadi et al., 2017) or
that a price level is inconsistent with the value of the
corresponding offering (Xia and Monroe, 2010).
Second, our model does not incorporate contingency
variables or variables related to individual characteris-
tics (income, price sensitivity, familiarity with RM, etc.)
and socio-demographics (age, gender, occupation, etc.).
However, previous research (e.g. Heo and Lee, 2011)
has shown that individual consumer characteristics and
certain contingency factors (e.g. state of the competi-
tion, the customer’s nationality and culture, etc.) play an
important role in the perception of RMP. The inclusion
of situational variables would have been helpful to find
out whether these variables have an impact on the per-
ception of revenue management and on the WTP prices
based on this technique. Third, methodological limita-
tions also need to be taken into consideration. The sce-
narios proposed in the experimental design are likely
to be biased. Even though our scenarios were con-
structed with the utmost rigour and with the aid of pro-
fessionals, these tools nevertheless remain theoretical
frameworks whose practical application in ‘real life’
may not yield the same results as those of this study.
Their testing under real-life conditions in hotels will
be needed to demonstrate their robustness. Moreover,
the samples used in this research are not perfectly rep-
resentative, with some socio-professional categories
such as retirees poorly represented (4%).
Prospects and avenues for future
research
We will conclude this article with some suggestions
for future research. First, we suggest that the scale for
measuring perceived unfairness be retested in other
contexts to test its performance and especially its
external validity. The deployment of this instrument
on other RMP issues and in other sectors (e.g. rail
transport, catering, theme parks, etc.) would be a way
of confirming its reliability and its internal and exter-
nal validity. With respect to reducing perceived
unfairness and improving WTP, we suggest that other
policy levers for reducing perceived unfairness in
RMP be explored. These might include, for example,
levers relating to ethics, procedural justice and inter-
actional justice that were not addressed in this
research. Levers based on the perceived value of sup-
ply (Rivière and Mencarelli, 2012) are also avenues
of research to be explored. Furthermore, future
research should carry out experiments regarding our
fairness-based pricing model under real conditions.
These new tests could establish the operational effi-
ciency of the two models. It would, for example,
involve working with hotels that agree to commit to
a pricing approach based on fairness (benefit–cost
ratio) and transparency. Doing so would make it pos-
sible to measure the reactions of ‘real’ customers to
an RMP model based on both equity and transpar-
ency as independent variables and a second model
based on equity as the independent variable and
transparency as the moderating variable. Our research
thus opens up new avenues of investigation regard-
ing strategies to reduce the perceived unfairness of
RMP policies and the regarding levers of action that
can be mobilized to promote WTP. Furthermore,
mediation tests (e.g. the mediating role of perceived
unfairness in the relationship between perceived
equity and WTP) and other moderation tests (e.g. the
moderating effects of individual consumer variables)
are also avenues to be explored in future research.
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20 Recherche et Applications en Marketing (English Edition) 00(0)
Appendix 1. Definitions of terms used in RM research.
Revenue management Yield management Pricing or RMP
RM is a comprehensive strategy for
forecasting, optimizing and controlling
capacity, prices and turnover in
companies with capacity constraints
and perishable assets (Buckhiestern,
2011; Weatherford and Bodily, 1992).
The aim of yield management
is to manage unit revenues
through an optimal allocation
of capacity by tariff class
(Capiez, 2003; Legohérel
etal., 2013).
The purpose of RMP is to
organize and manage the pricing
policy and price grids according
to the overall objectives set
within the framework of RM
(Heo and Lee, 2011).
RMP or pricing is a component of revenue management (RM). RM involves more than pricing alone and makes use of other levers
such as overbooking, distribution management and performance analysis (Kimes, 1994).
RMP: revenue management pricing.
Appendix 2. Maxwell’s (2002) WTP (Willingness To Pay) scale with French translation.
Original items in English Traduction en français
The likelihood of my purchasing this ticket is . . . La probabilité que j’achète ce billet est . . .
My willingness to buy the ticket is . . . Mon intention de payer ce billet est . . .
The probability that I would consider buying this ticket is . . . La probabilité pour moi d’acheter ce billet est . . .
Appendix 3. Presentation of the factorial design and research stimuli.
Under the first condition (Scenario 1), price equity and transparency of information are simultaneously tested to measure interac-
tion effects. Under the second condition (Scenario 2), only transparency is tested to measure its individual effects. Under the third
condition (Scenario 3), only equity is tested. Finally, under the fourth condition (Scenario 4), equity and transparency were both
removed in order to measure the effects of their joint absence on the dependent variables.
Méatchi and Camus 21
Appendix 4. Reliability and validity of endogenous and exogenous model variables.
Latent variables Reflective indicators (items) Loadings
Cronbach’s
alpha (α)
DG
rho (p)
AVE
(Average
Variance
Extracted)
Perceived price equity (PPE) Proportional price 0.90 0.81 0.88 0.71
Impartial price 0.71
Justified price 0.91
Perceived transparency of
information (PTI)
Clear information 0.66 0.65 0.81 0.57
Explanation 0.70
Accurate information 0.88
Cognitive dimension of
perceived unfairness (CDU)
These prices are unacceptable 0.89 0.89 0.92 0.70
These prices are dishonest 0.83
These prices are outrageous 0.85
These prices are incomprehensible 0.82
These prices do not make sense 0.79
Affective dimension of
perceived unfairness (ADU)
We are being duped 0.79 0.74 0.85 0.66
They are laughing at us 0.81
We are being manipulated 0.83
Willingness to pay (WTP) I accept these prices 0.84 0.74 0.85 0.65
I am willing to pay these prices 0.81
I agree to pay these prices 0.78
DG: Dillon–Goldstein.
Appendix 5. Summary of latent variable scores for Model 1.
1. Scores of the individual effects of perceived equity (PPE) and perceived transparency (PTI) on the cognitive
dimension of perceived unfairness (CDU)
R² (CDU/1) F Pr > F R² (bootstrap) Standard error Critical ratio
0.68 289.23 0.00 0.69 0.06 10.55
Path coefficients (CDU/1)
Latent variable Value Standard error t Pr > |t|f2
PPE 0.76 0.03 21.70 0.00 1.70
PTI 0.20 0.03 5.66 0.00 0.12
2. Scores of the individual effects of perceived equity (PPE) and perceived transparency (PTI) on the affective dimen-
sion of perceived unfairness (ADU)
R² (ADU/1) F Pr > F R² (bootstrap) Standard error Critical ratio
0.16 26.27 0.00 0.22 0.08 2.00
(Continued)
22 Recherche et Applications en Marketing (English Edition) 00(0)
Path coefficients (ADU/1)
Latent variable Value Standard error t Pr > |t|f2
PPE −0.38 0.06 −6.68 0.00 0.16
PTI 0.23 0.06 4.14 0.00 0.06
3. Scores of individual effects of perceived equity (PPE) and perceived transparency (PTI) on willingness to pay (WTP)
R² (WTP/1) F Pr > F R² (bootstrap) Standard error Critical ratio
0.71 344.94 0.00 0.72 0.06 11.46
Path coefficients (WTP/1)
Latent variable Value Standard error t Pr > |t|f2
PPE 0.81 0.03 24.72 0.00 2.21
PTI 0.12 0.03 3.58 0.00 0.05
Appendix 5. (Continued)
Appendix 6. Summary of latent variable scores for Model 2.
1. Scores for the effects of interactions between perceived equity (PPE) and perceived transparency (PTI) on the cog-
nitive dimension of perceived unfairness (CDU)
R² (CDU/2) F Pr > F R² (bootstrap) Standard error Critical ratio (CR)
Path coefficients (DCU/2)
0.69 608.27 0.00 0.70 0.06 11.14
Latent variable Value Standard error t Pr > |t|f2
PPE × PTI 0.83 0.03 24.66 0.00 2.19
2. Scores for the effects of interactions between perceived equity (PPE) and perceived transparency (PTI) on the af-
fective dimension of perceived unfairness (ADU)
R² (ADU/2) F Pr > F R² (bootstrap) Standard error Critical ratio (CR)
0.20 68.91 0.00 0.23 0.09 2.27
Path coefficients (ADU/2)
Latent variable Value Standard error t Pr > |t|f2
PPE × PTI −0.45 0.05 −8.30 0.00 0.25
3. Scores of the effects of interactions between perceived equity (PPE) and perceived transparency (PTI) on willing-
ness to pay (WTP)
R² (WTP/2) F Pr > F R² (bootstrap) Standard error Critical ratio (CR)
0.70 662.15 0.00 0.71 0.06 11.12
Path coefficients (WTP/2)
Latent variable Value Standard error t Pr > |t|f2
PPE × PTI 0.84 0.03 25.73 0.00 2.38
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